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Company Overview At 4A Consulting, we turn complexity into opportunity. Founded in 2014 and headquartered in Baltimore, MD, we are a women-owned, boutique consulting firm specializing in delivering innovative, data-driven solutions to both the Federal Government and Fortune 500 clients. Our team blends deep industry knowledge with advanced technologies to design tailored strategies that drive measurable and sustainable outcomes. We pride ourselves on an agile, collaborative approach that helps organizations navigate challenges and seize emerging opportunities in a rapidly evolving digital landscape. At 4A, we don't just deliver projects, we build trusted partnerships that empower our clients to lead with confidence in the digital age. Position Overview The AI/ML Platform Engineer will develop, maintain, and optimize the infrastructure, tools, and automated workflows supporting the state\'s shared enterprise AI/ML platform. The role focuses on ML pipeline automation, CI/CD, model deployment, monitoring, cloud cost optimization, and developer enablement. The engineer will collaborate with data scientists, data engineers, software developers, agency stakeholders, and external partners to deliver reliable, scalable, and production-ready AI/ML solutions across state agencies. Key Responsibilities ML Pipeline Automation and CI/CD: Build and maintain automated ML pipelines for data preprocessing, feature engineering, model training, evaluation, and deployment. Implement automated testing, pipeline validation, staged deployment, and failure recovery using Apache Airflow, Kubeflow Pipelines, Prefect, or equivalent tools. Model Development and Deployment: Prototype, implement, and optimize ML algorithms and integrate models into production systems. Apply appropriate supervised and unsupervised learning, deep learning, NLP, computer vision, and Generative AI techniques based on business requirements. Monitoring and Reliability: Implement logging, metrics, dashboards, and alerts to monitor pipeline health, model performance, data drift, model degradation, and infrastructure utilization. Participate in production support, incident response, troubleshooting, and root-cause analysis. Cloud Cost Optimization: Monitor compute, storage, and data-transfer costs. Optimize resource utilization through autoscaling, spot or preemptible instances, and workload scheduling. Contribute to infrastructure-as-code configurations, resource tagging, and budget controls. Developer Experience: Maintain internal SDKs, self-service tools, onboarding documentation, and reusable templates. Support platform users, troubleshoot issues, resolve bugs, and conduct technical enablement sessions for agency teams. Collaboration and Continuous Improvement: Translate business requirements into technical solutions, collaborate across multidisciplinary teams, evaluate emerging ML technologies, and improve platform reliability, scalability, usability, and operational efficiency. Required Qualifications Bachelor\'s degree in Computer Science, Engineering, or a related technical field. A master\'s degree or PhD is preferred but not required. At least five (5) years of experience in software engineering, data engineering, or ML engineering, including at least two (2) years working with production ML systems. Strong proficiency in Python and experience developing maintainable, production-quality code. Solid understanding of ML and deep learning fundamentals, including model training, evaluation, feature engineering, versioning, and deployment. Experience with ML frameworks and libraries such as PyTorch, TensorFlow, or scikit-learn, and with at least one ML orchestration tool: Apache Airflow, Kubeflow Pipelines, or Prefect. Familiarity with AWS, Azure, or GCP and managed AI/ML services. Experience with Docker, basic Kubernetes operations, and CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins. Experience building, deploying, monitoring, or troubleshooting ML pipelines and production workflows. Strong analytical, problem-solving, debugging, communication, and cross-functional collaboration skills. Preferred Qualifications Experience with monitoring and observability tools such as Prometheus, Grafana, or Datadog. Familiarity with experiment tracking and model management tools such as MLflow or Weights & Biases. Experience with infrastructure as code and configuration management using Terraform or Ansible. Familiarity with feature stores such as Feast or Tecton. Experience with internal developer tools, SDKs, and self-service platform capabilities. Knowledge of NLP, computer vision, speech processing, reinforcement learning, or Generative AI. Experience in government, regulated, or large enterprise environments. Skills and Competencies Strong attention to detail and commitment to operational reliability. Ability to independently troubleshoot complex pipelines and distributed systems. Clear technical documentation and incident reporting skills. Collaborative approach to working with engineers, data scientists, and nontechnical stakeholders. Continuous improvement mindset focused on reducing operational issues, deployment delays, and unnecessary cloud costs. Why Join 4A Be part of a mission-driven, women-owned consulting firm with a reputation for excellence. Work on high-impact projects across federal and commercial clients. Collaborate in an inclusive, growth-oriented culture where innovation is valued. Access career development programs, mentorship, and learning opportunities. Enjoy a comprehensive benefits package, flexible work options, and a focus on work-life balance. Equal Opportunity Statement 4A Consulting is an Equal Opportunity Employer committed to an inclusive hiring process. Applicants requiring a reasonable accommodation due to a disability may contact accommodations@4a-consulting.com. This email is intended solely for accommodation requests. Please note that 4A Consulting participates in the federal E-Verify program. Upon hire, we will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the US. 4A Consulting will only use E-Verify once you have accepted a job offer and completed the Form I-9.

Description Please note: This role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award. The Work At ICF our Digital Modernization Division is an information technology and management consulting organization that delivers integrated, strategic solutions to federal clients. We bring expertise in cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation to support mission-critical government programs. Join a team accelerating the modernization of a large federal agency's enterprise data and analytics ecosystem. This cloud-based platform provides data storage, analytics, governance, and AI/ML capabilities that enable thousands of users to transform data into actionable insights. As demand continues to grow, the team is focused on migrating legacy workloads, streamlining onboarding and support, expanding platform capabilities, and helping organizations across the enterprise adopt modern data and AI solutions at scale. The ML Ops Engineer will develop and maintain machine learning pipelines, model registries, deployment frameworks, monitoring solutions, and automated workflows that support enterprise AI initiatives. Working closely with data scientists, data engineers, cloud architects, platform engineers, and Trustworthy AI stakeholders, this role enables the successful operationalization of machine learning capabilities across cloud-based environments. Job Location: Remote, however, strong preference for candidates who live in the Washington DC Metro Area. There will be occasional onsite meetings on the client site in Washington, DC. If you accept this position, you should note that ICF does monitor employee work locations, blocks access from foreign locations/foreign IP addresses, and prohibits personal VPN connections. What You'll Do Design, build, and maintain production-grade MLOps pipelines for model training, evaluation, validation, registration, deployment, monitoring, retraining, rollback, and retirement. Develop reusable MLOps and LLMOps patterns using Azure Databricks, Databricks ML, MLflow, Unity Catalog, Azure Machine Learning, Python, and approved Azure AI services. Implement experiment tracking, model versioning, model registries, lineage, quality metrics, model cards, and approval workflows using MLflow and Unity Catalog to ensure models are discoverable, reusable, and auditable. Build automated CI/CD pipelines using GitHub Actions, Azure DevOps, Databricks Asset Bundles, and Terraform to promote models, code, configurations, and supporting infrastructure consistently across development, test, and production environments. Deploy and maintain scalable model-serving infrastructure for batch, streaming, real-time, and API-based inference workloads using Databricks Model Serving, Azure Machine Learning, Databricks compute, serverless capabilities, and GPU-enabled configurations, as applicable. Establish automated testing and evaluation gates for model performance, data quality, fairness, safety, explainability, robustness, privacy, and release readiness. Implement model and feature monitoring, drift and bias detection, logging, tracing, alerting, and operational dashboards using MLflow Model Monitoring, Lakehouse Monitoring, and the broader platform monitoring stack. Develop automated retraining, champion/challenger promotion, rollback, and model-retirement workflows that prevent performance degradation and support reliable production operations. Integrate ML workflows with source control, infrastructure provisioning, secrets management, identity and access controls, environment management, and enterprise release processes. Implement Trustworthy AI controls, including model documentation, impact assessments, audit logging, content safeguards, human oversight, and evaluation evidence aligned with Government-approved standards and the NIST AI Risk Management Framework. Partner with data scientists, AI engineers, data engineers, platform engineers, DevSecOps, Security, and Governance personnel to make models repeatable, testable, deployable, and operationally supportable. Monitor compute and serving utilization, tune cluster and endpoint configurations, apply tagging conventions, and implement cost-optimization strategies for training and inference workloads. Troubleshoot failed pipelines, deployment issues, model-serving incidents, performance degradation, and monitoring alerts while supporting root-cause analysis and corrective actions. Create and maintain deployment templates, reusable repositories, operational runbooks, model documentation, release evidence, and technical standards that accelerate responsible AI/ML adoption across the enterprise. Basic Qualifications U.S. Citizenship is required due to federal contract requirements. Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S. Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years. Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, Engineering, or a related field or a high school diploma with four (4) additional years of relevant experience in lieu of a bachelor's degree. 6+ years of experience designing and supporting production machine learning solutions in cloud environments. Master's degree may substitute for two (2) years of relevant experience. Preferred Qualifications Experience with machine learning operations (MLOps), automated deployment pipelines, and model lifecycle management. Proficiency in Python and modern software development practices. Experience with source control systems and CI/CD frameworks. Hands-on experience with Azure Machine Learning, Databricks, MLflow, or comparable ML platforms. Experience implementing model monitoring, automated retraining, and performance tracking solutions. Knowledge of cloud-native architecture, containerization, and scalable model serving patterns. Experience supporting Responsible AI, AI governance, or Trustworthy AI initiatives. Familiarity with infrastructure-as-code and automated environment provisioning. Strong understanding of cloud cost optimization practices for AI/ML workloads. #Indeed Bot and Third-Party Applications Please note that this application must be submitted directly by the applicant for consideration. Failure to do so may result in the application being excluded for consideration. Applicants needing an accommodation for disability or religious purposes in connection with the application process should contact Candidateaccommodation@icf.com for assistance. Working at ICF ICF is a global advisory and technology services provider, but we're not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future. We can only solve the world's toughest challenges by building a workplace that allows everyone to thrive. We are an equal opportunity employer. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. For more information, please read our EEO policy. We will consider for employment qualified applicants with arrest and conviction records. Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process. To request an accommodation, please email Candidateaccommodation@icf.com and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. Read more about workplace discrimination rights or our benefit offerings which are included in the Transparency in (Benefits) Coverage Act. Candidate AI Usage Policy At ICF, we are committed to ensuring a fair interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process. However, we understand that some candidates may require accommodation that involves the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed. Pay Range There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position. The pay range for this position based on full-time employment is: $98,614.00 - $167,644.00 Nationwide Remote Office (US99)

Description Please note: This role is contingent upon a contract award. While it is not an immediate opening, we are actively conducting interviews and extending offers in anticipation of the award. The Work At ICF our Digital Modernization Division is an information technology and management consulting organization that delivers integrated, strategic solutions to federal clients. We bring expertise in cloud, cybersecurity, enterprise architecture, data modernization, and digital transformation to support mission-critical government programs. Join a team accelerating the modernization of a large federal agency's enterprise data and analytics ecosystem. This cloud-based platform provides data storage, analytics, governance, and AI/ML capabilities that enable thousands of users to transform data into actionable insights. As demand continues to grow, the team is focused on migrating legacy workloads, streamlining onboarding and support, expanding platform capabilities, and helping organizations across the enterprise adopt modern data and AI solutions at scale. The ML Ops Engineer will develop and maintain machine learning pipelines, model registries, deployment frameworks, monitoring solutions, and automated workflows that support enterprise AI initiatives. Working closely with data scientists, data engineers, cloud architects, platform engineers, and Trustworthy AI stakeholders, this role enables the successful operationalization of machine learning capabilities across cloud-based environments. Job Location: Remote, however, strong preference for candidates who live in the Washington DC Metro Area. There will be occasional onsite meetings on the client site in Washington, DC. If you accept this position, you should note that ICF does monitor employee work locations, blocks access from foreign locations/foreign IP addresses, and prohibits personal VPN connections. What You'll Do Design, build, and maintain production-grade MLOps pipelines for model training, evaluation, validation, registration, deployment, monitoring, retraining, rollback, and retirement. Develop reusable MLOps and LLMOps patterns using Azure Databricks, Databricks ML, MLflow, Unity Catalog, Azure Machine Learning, Python, and approved Azure AI services. Implement experiment tracking, model versioning, model registries, lineage, quality metrics, model cards, and approval workflows using MLflow and Unity Catalog to ensure models are discoverable, reusable, and auditable. Build automated CI/CD pipelines using GitHub Actions, Azure DevOps, Databricks Asset Bundles, and Terraform to promote models, code, configurations, and supporting infrastructure consistently across development, test, and production environments. Deploy and maintain scalable model-serving infrastructure for batch, streaming, real-time, and API-based inference workloads using Databricks Model Serving, Azure Machine Learning, Databricks compute, serverless capabilities, and GPU-enabled configurations, as applicable. Establish automated testing and evaluation gates for model performance, data quality, fairness, safety, explainability, robustness, privacy, and release readiness. Implement model and feature monitoring, drift and bias detection, logging, tracing, alerting, and operational dashboards using MLflow Model Monitoring, Lakehouse Monitoring, and the broader platform monitoring stack. Develop automated retraining, champion/challenger promotion, rollback, and model-retirement workflows that prevent performance degradation and support reliable production operations. Integrate ML workflows with source control, infrastructure provisioning, secrets management, identity and access controls, environment management, and enterprise release processes. Implement Trustworthy AI controls, including model documentation, impact assessments, audit logging, content safeguards, human oversight, and evaluation evidence aligned with Government-approved standards and the NIST AI Risk Management Framework. Partner with data scientists, AI engineers, data engineers, platform engineers, DevSecOps, Security, and Governance personnel to make models repeatable, testable, deployable, and operationally supportable. Monitor compute and serving utilization, tune cluster and endpoint configurations, apply tagging conventions, and implement cost-optimization strategies for training and inference workloads. Troubleshoot failed pipelines, deployment issues, model-serving incidents, performance degradation, and monitoring alerts while supporting root-cause analysis and corrective actions. Create and maintain deployment templates, reusable repositories, operational runbooks, model documentation, release evidence, and technical standards that accelerate responsible AI/ML adoption across the enterprise. Basic Qualifications U.S. Citizenship is required due to federal contract requirements. Candidate must reside in the U.S., be authorized to work in the U.S., and all work must be performed in the U.S. Candidate must have lived in the U.S. for three (3) full years out of the last five (5) years. Bachelor's degree in Computer Science, Software Engineering, Machine Learning, Data Science, Engineering, or a related field or a high school diploma with four (4) additional years of relevant experience in lieu of a bachelor's degree. 6+ years of experience designing and supporting production machine learning solutions in cloud environments. Master's degree may substitute for two (2) years of relevant experience. Preferred Qualifications Experience with machine learning operations (MLOps), automated deployment pipelines, and model lifecycle management. Proficiency in Python and modern software development practices. Experience with source control systems and CI/CD frameworks. Hands-on experience with Azure Machine Learning, Databricks, MLflow, or comparable ML platforms. Experience implementing model monitoring, automated retraining, and performance tracking solutions. Knowledge of cloud-native architecture, containerization, and scalable model serving patterns. Experience supporting Responsible AI, AI governance, or Trustworthy AI initiatives. Familiarity with infrastructure-as-code and automated environment provisioning. Strong understanding of cloud cost optimization practices for AI/ML workloads. #Indeed Bot and Third-Party Applications Please note that this application must be submitted directly by the applicant for consideration. Failure to do so may result in the application being excluded for consideration. Applicants needing an accommodation for disability or religious purposes in connection with the application process should contact Candidateaccommodation@icf.com for assistance. Working at ICF ICF is a global advisory and technology services provider, but we're not your typical consultants. We combine unmatched expertise with cutting-edge technology to help clients solve their most complex challenges, navigate change, and shape the future. We can only solve the world's toughest challenges by building a workplace that allows everyone to thrive. We are an equal opportunity employer. Together, our employees are empowered to share their expertise and collaborate with others to achieve personal and professional goals. For more information, please read our EEO policy. We will consider for employment qualified applicants with arrest and conviction records. Reasonable Accommodations are available, including, but not limited to, for disabled veterans, individuals with disabilities, and individuals with sincerely held religious beliefs, in all phases of the application and employment process. To request an accommodation, please email Candidateaccommodation@icf.com and we will be happy to assist. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. Read more about workplace discrimination rights or our benefit offerings which are included in the Transparency in (Benefits) Coverage Act. Candidate AI Usage Policy At ICF, we are committed to ensuring a fair interview process for all candidates based on their own skills and knowledge. As part of this commitment, the use of artificial intelligence (AI) tools to generate or assist with responses during interviews (whether in-person or virtual) is not permitted. This policy is in place to maintain the integrity and authenticity of the interview process. However, we understand that some candidates may require accommodation that involves the use of AI. If such an accommodation is needed, candidates are instructed to contact us in advance at candidateaccommodation@icf.com. We are dedicated to providing the necessary support to ensure that all candidates have an equal opportunity to succeed. Pay Range There are multiple factors that are considered in determining final pay for a position, including, but not limited to, relevant work experience, skills, certifications and competencies that align to the specified role, geographic location, education and certifications as well as contract provisions regarding labor categories that are specific to the position. The pay range for this position based on full-time employment is: $98,614.00 - $167,644.00 Nationwide Remote Office (US99)

AI & Tech Breadcrumb Home > Generative AI Consultant Generative AI Consultant 415 Mission Street, 94105 San Francisco, United States I'm interested Share this job Company Description About Sia Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We're optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. Sia's AI & Data Business Unit is the powerhouse of our firm's innovation—merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia's AI & Data team, you'll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. Job Description Join us as an experienced Generative AI Specialist designing and implementing cutting-edge GenAI/LLM solutions across diverse industries. You'll act as a vital bridge between technical teams (Data Science, ML, Platform) to deliver business-centric AI value. You'll guide clients on the optimal path—using techniques like RAG, agents, or fine-tuning—for cost-effective impact. Your responsibilities extend beyond prompting to architecting robust AI products via benchmarking, prototyping, and validation. You'll orchestrate the full AI workflow, ensuring seamless model integration optimized for performance, security, and scale, while tackling infrastructure challenges. We provide extensive training to support your success. If you're driven to push AI boundaries and help clients rapidly adopt GenAI with confidence, apply to make a real difference. Responsibilities LLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques. Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications. Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.). Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions. RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution). Model Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities. Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP). Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes. Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing. Collaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical). Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference. Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). Qualifications Education : Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field. Experience: 1-3+ years of hands-on experience in machine learning, software engineering, or data science, with demonstrated experience on complex AI projects specifically involving LLMs and Generative AI. Required Technical Skills Strong programming skills, particularly in Python. Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.). Proven experience in NLP/NLU, vector embeddings, and semantic search. Hands-on experience with fine-tuning LLMs. Mastery of advanced prompting techniques (Chain/Tree/Graph of Thought, ReAct, etc.). Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, models hosted on AWS/Azure/GCP, etc.). Experience with Cloud platforms (AWS, Azure, or GCP) and their associated MLOps/AI services. Familiarity with MLOps principles, CI/CD tools, Docker, and Git. Soft Skills Excellent communication skills (written and verbal), ability to explain complex technical concepts simply. Strong analytical and complex problem-solving abilities. Team player with the ability to collaborate effectively with diverse profiles. Curiosity, pioneering spirit, and a demonstrated commitment to continuous learning. Preferred Qualifications Experience building agentic AI systems (e.g., LangGraph, AutoGen). Experience with vector databases (e.g., pgvector, Pinecone, Chroma, OpenSearch). Experience developing conversational AI systems / chatbots. Familiarity with deep learning frameworks (PyTorch, TensorFlow). Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as Model Context Protocol (MCP). Experience deploying models at scale in production environments. Additional information Compensation & Benefits Base salary starting at $105,000, commensurate with experience and qualifications Annual Discretionary Bonus Healthcare coverage that includes 3 medical plan options: Anthem – EPO HSA, EPO HSA MERP, and PPO; dental and vision through MetLife; and life insurance policies through Mutual of Omaha Flexible Spending Account (FSA) Paid Time Off Parental leave paid at 100% of base pay for all new parents 9 Company Holidays + 1 Floating Holiday 401(k) Plan - 4% matching and vested on day 1 College save-up plan & college loan repayment plan Monthly cell phone stipend Pre-tax account for Parking and Mass Transit Sia provides several wellness and incentive programs free of charge through the firm medical plan – Anthem - such as: Gym Reimbursement LiveHealth Online Well-being Coach Building Healthy Families Program And much more Diversity, Equity, Inclusion & Belonging At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. Office Workplace Guidelines Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco—are expected to live within a reasonable commuting distance and attend the office at least three days per week. For Consultants outside of our primary markets, we can offer more flexible in-person requirements in accordance with your location. Work Authorization & Sponsorship At this time, Sia does not intend to pursue employment with applicants who will require now or in the future visa by our company for work authorization in the United States (i.e., H1-B visa, F-1 visa (OPT), TN visa, or any other non-immigrant status). Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. I'm interested

At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The O pportunity Supports the delivery of solution or infrastructure development services for AI/ML initiatives, applying strong technical capability and hands-on engineering experience. Contributes to the design, development, delivery, and maintenance of AI-enabled solutions or infrastructure while aligning to relevant engineering standards and project delivery expectations. Contributes to the integration of AI/ML capabilities into broader enterprise solutions, with a focus on quality, scalability, and user impact. Your Key Responsibilities Develop, test, and deploy, production-grade AI/ML, generative AI, and intelligent automation solutions. Support building and integrating LLM, RAG, and agentic solution components into enterprise applications and platforms. Support project delivery through disciplined execution, documentation, and status communication. Use modern AI-assisted software engineering tools such as Claude Code, Codex, or equivalent agentic coding platforms as part of day-to-day engineering delivery to improve delivery speed, code quality and engineering efficiency. AI and Engineering Skills: Gen AI Foundational: Demonstrated experience building retrieval-augmented systems that ground model outputs in enterprise knowledge sources, including chunking strategies, embedding pipelines, and retrieval optimization (e.g. LlamaIndex, LangChain, Pinecone, Weaviate, Azure AI Search, pgvector etc). Knowledge of embedding models, vector search, and semantic retrieval patterns used to ground LLM outputs in enterprise knowledge sources (e.g. OpenAI Embeddings, Azure AI Search, pgvector etc). Experience in prompt engineering techniques including zero-shot, few-shot, chain-of-thought, and structured output design, with the ability to systematically evaluate and iterate on prompt performance (e.g. DSPy, PromptFlow etc). Agentic and LLM Ops: Experience designing and building agentic systems including multi-agent orchestration patterns, tool use, and memory design across single and multi-step workflows (e.g. LangGraph, AutoGen, CrewAI, Semantic Kernel, NVIDIA NIM etc) Software Engineering: Hands-on software engineering proficiency in Python, with the ability to write clean, modular, production-quality code for LLM pipelines and agentic applications. Experience working with structured and unstructured data sets to support LLM application development, including data curation, preparation, and quality validation for model inputs. Familiarity with RESTful and event-driven API patterns including asynchronous workflows, service boundaries, and integration of enterprise data sources to expose LLM and agentic capabilities. Familiarity with containerization and orchestration concepts for packaging and deploying LLM applications in cloud environments (e.g. Docker, Kubernetes, Azure Container Apps, AWS ECS etc). Understanding of software engineering best practices as applied to ML systems, including modular code design, testing patterns for AI pipelines, and data quality validation. Soft Skills and additional attributes for success: Able to operate effectively as requirements, regulations, and technologies evolve. Collaborative and cross‑functional, working closely with engineering teams. Bachelor's degree preferred. 1+ years of applied engineering experience, including meaningful experience in AI/ML engineering roles. Demonstrated experience in the following areas will be a huge plus: Ability to understand business challenges and translate them into value-add AI solutions leveraging large language models and intelligent automation. Experience designing, building, and maintaining production-grade LLM applications, including end-to-end pipelines from data ingestion through model output delivery (e.g. Azure OpenAI, AWS Bedrock, Google Vertex AI etc). Familiarity with CI/CD and operationalization practices for AI systems, including model and workflow deployment, versioning, environment promotion, and release support in cloud or containerized environments. Familiarity with LLM fine-tuning approaches including instruction tuning and preference optimization, with an understanding of when fine-tuning is appropriate versus prompt-based solutions (e.g. LoRA, QLoRA, PEFT, NeMo Framework etc). Familiarity with responsible AI principles including bias and fairness evaluation, human-in-the-loop design, and explainability approaches in the financial services contexts. Familiarity with data pipeline design for AI workloads including ingestion, transformation, and quality validation. Familiarity with cloud-based platforms for building, training, and deploying scalable LLM solutions (e.g. Azure ML, AWS SageMaker, Google Vertex AI etc). What We Offer You At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers. We offer a comprehensive compensation and benefits package where you'll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job is: New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $56,000 to $103,800 Bay Area California offices – $58,300 to $108,100 All other offices locations in the US, including Sacramento – $46,700 to $95,200 Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Under our flexible vacation policy, you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being. Are you ready to shape your future with confidence? Apply today. To make the most of your application experience, please limit yourself to two applications within a six-month period. EY accepts applications for this position on an on-going basis. For those living in California, please click here for additional information. At EY, our values set the foundation for how we work and the behaviors we expect of our people. Any misrepresentation or falsification of information or lack of integrity at any point in the recruiting process may result in withdrawal of your candidacy, revocation of an offer or immediate termination of employment. EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories. All in to shape the future with confidence. EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at ssc.customersupport@ey.com.

About Sia Sia is a next-generation, global management consulting group. Founded in 1999, we were born digital. Today our strategy and management capabilities are augmented by data science, enhanced by creativity and driven by responsibility. We're optimists for change and we help clients initiate, navigate and benefit from transformation. We believe optimism is a force multiplier, helping clients to mitigate downside and maximize opportunity. With expertise across a broad range of sectors and services, our 3,000 consultants serve clients worldwide from 48 locations in 19 countries. Our expertise delivers results. Our optimism transforms outcomes. Sia's AI & Data Business Unit is the powerhouse of our firm's innovation—merging cutting-edge Data Science, Generative AI, and advanced digital solutions to transform industries. With over 350 experts worldwide, we tackle projects from proof-of-concept to large-scale deployment, always pushing the boundaries of AI capabilities. Our 12 R&D labs in Europe and North America drive continuous research in areas like computer vision, MLOps, and deep learning, partnering closely with our business consultants for real-world impact. By joining Sia's AI & Data team, you'll step into a vibrant, collaborative environment that nurtures professional growth and empowers you to shape the future of AI-driven consulting. Job Description Join us as an experienced Generative AI Specialist designing and implementing cutting-edge GenAI/LLM solutions across diverse industries. You'll act as a vital bridge between technical teams (Data Science, ML, Platform) to deliver business-centric AI value. You'll guide clients on the optimal path—using techniques like RAG, agents, or fine-tuning—for cost-effective impact. Your responsibilities extend beyond prompting to architecting robust AI products via benchmarking, prototyping, and validation. You'll orchestrate the full AI workflow, ensuring seamless model integration optimized for performance, security, and scale, while tackling infrastructure challenges. We provide extensive training to support your success. If you're driven to push AI boundaries and help clients rapidly adopt GenAI with confidence, apply to make a real difference. Responsibilities: LLM/GenAI System Development: Design, build, train, fine-tune, and deploy sophisticated AI models leveraging LLMs (e.g., GPT-x, Claude, Gemini, Llama, Mistral) and other generative techniques. Assist in Solution Architecture: Support the GenAI Solution Architect in designing robust, scalable, and secure applications. Application Development: Develop applications powered by GenAI models (both self-managed and API-accessible) that meet business needs and comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.). Advanced Prompt Engineering: Design and optimize effective prompts (e.g., few-shot, Chain/Tree/Graph of Thought, ReAct, Self-reflection, guardrails), balancing simplicity and complexity to enhance analytical capabilities, refine outputs, improve user experience, and control interactions. RAG Implementation: Design and implement Retrieval-Augmented Generation (RAG) architectures to improve accuracy and relevance by retrieving information from pre-determined knowledge sources, providing traceability (source attribution). Model Selection & Fine-Tuning: Select and fine-tune appropriate models (including multimodal - VLM, SLM - Visual Language Models, Small Language Models) to create higher-quality content (text, image, audio, code, etc.) and maximize business value creation opportunities. Integration & Deployment (MLOps): Implement MLOps best practices for the GenAI lifecycle, including automated pipelines (CI/CD), versioning, monitoring, and maintenance in production environments (Cloud platforms like AWS, Azure, GCP). Ensure seamless integration into existing systems and with external tools/APIs, potentially utilizing standardized protocols (MCP). Evaluation & Responsible AI: Develop and execute rigorous evaluation frameworks to measure model performance, reliability, fairness, and safety. Ensure adherence to Responsible AI principles and help teams and clients navigate end-to-end security and compliance processes. Research & Innovation: Stay abreast of the latest advancements in GenAI techniques, technologies, and frameworks. Experiment with new approaches and contribute to internal knowledge sharing. Collaboration: Work effectively within cross-functional teams, communicating complex technical concepts clearly to diverse stakeholders (both technical and non-technical). Documentation: Document processes, methodologies, and best practices for knowledge sharing and future reference. Use Case Differentiation: Distinguish between use cases suited for Generative AI versus traditional NLP applications (e.g., NER, sentiment analysis). Qualifications Education : Master's degree or Engineering degree (or equivalent) in Computer Science, Engineering, Data Science, or a related quantitative field. Experience: 1-3+ years of hands-on experience in machine learning, software engineering, or data science, with demonstrated experience on complex AI projects specifically involving LLMs and Generative AI. Required Technical Skills: Strong programming skills, particularly in Python. Proficiency in at least one major GenAI application framework (LangChain, LlamaIndex, etc.). Proven experience in NLP/NLU, vector embeddings, and semantic search. Hands-on experience with fine-tuning LLMs. Mastery of advanced prompting techniques (Chain/Tree/Graph of Thought, ReAct, etc.). Knowledge of both proprietary and open-source model ecosystems (OpenAI, Anthropic, Mistral AI, Hugging Face, models hosted on AWS/Azure/GCP, etc.). Experience with Cloud platforms (AWS, Azure, or GCP) and their associated MLOps/AI services. Familiarity with MLOps principles, CI/CD tools, Docker, and Git. Soft Skills: Excellent communication skills (written and verbal), ability to explain complex technical concepts simply. Strong analytical and complex problem-solving abilities. Team player with the ability to collaborate effectively with diverse profiles. Curiosity, pioneering spirit, and a demonstrated commitment to continuous learning. Preferred Qualifications: Experience building agentic AI systems (e.g., LangGraph, AutoGen). Experience with vector databases (e.g., pgvector, Pinecone, Chroma, OpenSearch). Experience developing conversational AI systems / chatbots. Familiarity with deep learning frameworks (PyTorch, TensorFlow). Understanding of or experience with protocols and standards for connecting LLMs to external tools and databases, such as Model Context Protocol (MCP). Experience deploying models at scale in production environments. Additional Information Compensation & Benefits Base salary starting at $105,000, commensurate with experience and qualifications Annual Discretionary Bonus Healthcare coverage that includes 3 medical plan options: Anthem – EPO HSA, EPO HSA MERP, and PPO; dental and vision through MetLife; and life insurance policies through Mutual of Omaha Flexible Spending Account (FSA) Paid Time Off Parental leave paid at 100% of base pay for all new parents 9 Company Holidays + 1 Floating Holiday 401(k) Plan - 4% matching and vested on day 1 College save-up plan & college loan repayment plan Monthly cell phone stipend Pre-tax account for Parking and Mass Transit Sia provides several wellness and incentive programs free of charge through the firm medical plan – Anthem - such as: Gym Reimbursement LiveHealth Online Well-being Coach Building Healthy Families Program And much more Diversity, Equity, Inclusion & Belonging At Sia, we believe in fostering a diverse, equitable and inclusive culture where our employees and partners are valued and thrive in a sense of belonging. We are committed to recruiting and developing a diverse network of employees and investing in their growth by providing unique opportunities for professional and cultural immersion. Our commitment toward inclusion motivates dynamic collaboration with our clients, building trust by creating an inclusive environment of curiosity and learning which affects lasting impact. Please visit our website for more information. Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. Office Workplace Guidelines Sia is committed to providing a flexible workplace environment that supports client, business, and market needs. Consultants located in our primary market office locations—New York City, Charlotte, Seattle, and San Francisco—are expected to live within a reasonable commuting distance and attend the office at least three days per week. For Consultants outside of our primary markets, we can offer more flexible in-person requirements in accordance with your location. Work Authorization & Sponsorship At this time, Sia does not intend to pursue employment with applicants who will require now or in the future visa by our company for work authorization in the United States (i.e., H1-B visa, F-1 visa (OPT), TN visa, or any other non-immigrant status). Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! You are: A Context Engineer, pivotal in orchestrating the delivery of AI-driven solutions - bridging business analysis, solution design, and integration to ensure AI has the right context to produce consistently strong, mission-aligned results. You translate approved user stories into AFS-compliant agent prompts, designs and governs the subagents that execute them, operates the AI build pipeline, and owns a high-performing prompt library. You integrate seamlessly with CI/CD pipelines while upholding security and ATO (Authority to Operate) compliance standards. The work: Translate approved user stories into AFS-compliant agent prompts, ensuring alignment with project objectives and mission outcomes. Design the architecture for specialized subagents that operate within the build pipeline - defining each agent's purpose, scope, tools, and boundaries. Build routing, delegation, and escalation logic that determines when the system answers directly, invokes a subagent, runs specialists in parallel, asks a clarifying question, uses a tool, escalates to a human, or declines an unsafe action. Define agent-to-subagent contracts: inputs, context boundaries, structured outputs, confidence and evidence, latency budgets, cancellation behavior, and failure handling. Configure, manage, and operate AI build pipelines using generative agentic tools and orchestration frameworks (e.g., Claude, Codex, LangGraph). Own and maintain the prompt library including version control, quality scoring, and continuous improvement - refining prompts based on reviewed outputs and feedback. Create and maintain RAG knowledge bases and query prior context files for precedent and predictive insight before authoring new prompts. Oversee and integrate CI/CD pipelines, embedding security validations (SAST, vulnerability scanning) and automated ATO evidence generation for seamless compliance. Build rapid prototypes using AI-assisted coding to test complex prompting and data workflows before full implementation. Document the work and enable others - producing clear write-ups and becoming the team's expert and trainer on prompting and context practices. Collaborate with cross-functional teams including AI Product Leads, Senior AI Engineers, and Verification Engineers to deliver AI solutions successfully. Here's what you need: Proven experience in business analysis, solution integration, or solution design. Strong background managing and configuring AI build pipelines with generative, agentic AI tooling and agent-orchestration frameworks - such as Claude, Codex, or LangGraph. Mastery of LLM prompting with hands-on API experience - command of prompt parameters, components, and conversational LLM outputs. Familiarity with CI/CD processes and tools, including security validation and compliance integration. Ability to query and analyze structured data and prior context files to derive actionable insights. Understanding of AI build pipelines, subagent orchestration, and RAG knowledge-base creation. Familiarity with version control systems and managing a prompt library. Experience working in agile environments or with scrum methodologies. Knowledge of security and compliance processes within the context of AI operations. Bonus points if you have: Bachelor's degree in Business, Information Systems, Computer Science, Engineering, or equivalent practical experience. Basic coding skills for rapid prototyping and iterating on data/prompting workflows. Multimodal prompting experience (images, video) and familiarity with text-embedding models. Copywriting, data science, or software engineering background. Prior work with conversational LLM outputs and feedback-driven prompt refinement. Excellent written communication - able to document work clearly and train others. Eligibility Requirements: U.S. Citizenship required. Ability to work with federal clients and comply with applicable AFS, client, security, and program requirements. Ability to work in a hybrid, remote, or client-site environment as program needs require. As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia . The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply. The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $64,000—$160,200 USD What We Believe As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on. Equal Employment Opportunity Statement We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the Accenture Federal Services Equal Opportunity Policy Statement. Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women. Requesting An Accommodation Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired. If you are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter. Other Employment Statements Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States. Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information. California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please click here for additional important information.

Position title: Conversational AI Specialist, VP New York Plaza, NYC Company Profile Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. The Firm's employees serve clients worldwide including corporations, governments and individuals from more than 1,200 offices in 43 countries. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence, and strong team ethic. Morgan Stanley can provide a superior foundation for building a professional career - a place for people to learn, to achieve and grow. A philosophy that balances personal lifestyles, perspectives and needs is an important part of our culture. About Firm Wide AI The Wealth Management Generative AI Team at Morgan Stanley is a dynamic and innovative department that serves as a Center of AI enablement. The team is responsible for deploying advanced systems that utilize generative artificial intelligence to optimize business processes. The team oversees governance and control measures to ensure the ethical and responsible use of AI technologies. The team is committed to fostering a culture of continuous learning and provide education on AI technologies to other departments within the company. Position Overview We are seeking a highly skilled and motivated Conversational AI Specialist with a strong background in conversational design and model evaluation to join our team at Morgan Stanley. In this role, you'll craft enterprise level conversational AI solutions, develop smart automation tools, and refine generative AI models to ensure reliable, quality outputs. This role will liaise with business teams across the Firm, technology, vendors, and centralized AI teams to accelerate the development and adoption of AI-based solutions. Key Responsibilities Conversational Experiences: Develop and maintain differentiated conversational experiences for employee and client virtual assistant experiences that allow users to access knowledge, data and workflows. Prompt Solutioning: Develop and refine context-aware prompts tailored to different use cases, domains, and user intents with a view of improving the accuracy, relevance and efficiency of AI generated chatbot responses. Ensure these prompt solutions are scalable, sustainable, effectively integrates with technical infrastructure, and successfully meet the specific needs of the business. Testing and Evaluation: Develop and maintain data driven methodologies for testing and evaluating Generative AI responses for coherence, bias, factual accuracy and user satisfaction. Create and manage human evaluations – manual and automated strategies such as LLM-as-a-judge – to ensure LLM Model outputs meet high standards. Troubleshooting and Optimization: Identify and troubleshoot issues and anomalies in the LLM model outputs and provide feedback and recommendations for solution improvement and optimization. Risk Management: Identify potential risks and issues that may impact project delivery and develop mitigation strategies to address them proactively. Monitor project performance and implement corrective actions as necessary to ensure successful outcomes. Stakeholder Management: Establish and maintain effective communication channels with internal stakeholders such as tech partners and business product owners. Manage expectations and address any concerns or issues that arise. Collaboration: Collaborate with cross-functional teams, including internal stakeholders and vendor partners. Performance Monitoring and Reporting: Track project performance metrics and KPIs to measure progress against objective and identify areas for improvement. Qualifications/Skills Required Or Preferred Experience with Conversational AI solutioning / product development / experimentation or Innovation. Experience with prompt engineering for using Commercial or Open Source LLMs such as GPT, Claude, Gemini, LLAMA. Experience with conversational AI evaluation techniques such as F1, RAGAS, and human feedback analysis. Strong understanding of artificial intelligence concepts and technologies. Excellent communication, interpersonal and leadership skills. Proven experience in program or project management Ability to manage multiple projects simultaneously in a fast-paced environment. Solid analytical and problem-solving abilities with keen attention to detail What You Can Expect From Morgan Stanley At Morgan Stanley, we raise, manage and allocate capital for our clients – helping them reach their goals. We do it in a way that's differentiated – and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work. To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser. Expected base pay rates for the role will be between $110,000 and $140,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs. Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents. Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences. For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! Build AI that matters . We ship production GenAI apps for confidential federal programs across defense, national security, public safety, civilian, and military health where reliability, privacy, and safety aren't optional. AFS is a technology company within global Accenture and a Glassdoor Top 100 Best Place to Work. You'll join a collaborative, inclusive community with hands-on growth, certifications, and industry training. We ship in weeks, not quarters, and measure success with latency, reliability, safety, and cost. Confidentiality matters: We don't disclose program details publicly. If you advance, we'll share specifics during the process. Role Overview You'll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You'll own the end-to-end path from use case evaluation → production deployment → operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale. What You'll Do (Day To Day) Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost. Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies. Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma). LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback. RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise. Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails. SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend. Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects. Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls. You'll Thrive Here If you have Built and deployed a production GenAI application (chatbot, copilot, assistant, or enterprise AI). Hands-on with LLMs GPT, Claude, Llama, Gemini, Mistral, via APIs or self-hosted. Designed and implemented RAG solutions using embeddings, vector databases, and semantic search for enterprise or mission data. Shipped AI applications with frameworks like LangChain, LangGraph, LlamaIndex, Semantic Kernel, DSPy, or similar. Strong Python development for building and integrating AI/ML applications. Owned AI solutions through full production life cycle, deployment and operational support. Active U.S. citizenship. Nice to Have Integration with leading cloud AI services or on prem inference stacks Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops. Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance. Experience implementing tool using agents for API integration and external data access. Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell). Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping. Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude). Contributions to internal frameworks or opensource; mentorship of engineers. Clear communication with engineers, PMs, and security/compliance stakeholders. As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia . The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply. The pay range for the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia is: $103,200—$203,400 USD What We Believe As a company wholly dedicated to serving the US federal government, we bring together the best talent to help reinvent how federal agencies operate and deliver greater value for their mission and the American people. We have an unwavering commitment to creating a culture in which all our people are respected, feel a sense of belonging, and have equal opportunity. As a business imperative, every person at Accenture Federal Services has the responsibility to create and sustain a culture where everyone feels welcomed and included. This is grounded in our core values and our experience that hiring and developing great people who reflect different perspectives, experiences, and backgrounds is key to driving innovation and delivering the results that our clients and the country count on. Equal Employment Opportunity Statement We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities. For details, view a copy of the Accenture Federal Services Equal Opportunity Policy Statement. Accenture Federal Services is an Equal Employment Opportunity employer. Additionally, as an Affirmative Action Employer for Veterans and Individuals with Disabilities, Accenture Federal Services is committed to providing veteran employment opportunities to our service men and women. Requesting An Accommodation Accenture Federal Services is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture Federal Services and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired. If you are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter. Other Employment Statements Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States. Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration. Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information. California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please click here for additional important information.

Description Do you love building data pipelines? Are you excited by the opportunity to design tools and infrastructure needed to analyze large volumes of data? Do you want to help solve big data warehousing problems, and partner with stakeholders to understand how to best design and implement data solutions that provide answers to key business questions? At Amazon, we hire the best minds in technology to innovate on behalf of our customers. The focus we have on our customers is why we are one of the world's most beloved brands – customer obsession is part of our company DNA. Data engineers use technology to solve complex problems and get to see the impact of their work first-hand. The challenges data engineers solve for at Amazon are big and impact millions of customers, sellers, and products around the world. Our path is not always simple, so we are selective about who joins us on this journey. There is a certain kind of person who takes on this role at Amazon – someone who is excited by the idea of creating new products, features, and services from scratch while managing ambiguity and the pace of a company whose ship cycles are measured in weeks, not years. A key focus of this role involves harnessing the power of Generative AI to optimize data source discovery and pipeline development, building intelligent agents to help Business Intelligence Engineers and Scientists identify emerging opportunities, creating self-service capabilities for stakeholders, and developing AI-integrated data platforms. We seek curious minds who think big and want to define tomorrow. Join us in creating solutions that change the world. Basic Qualifications 1+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) Experience with one or more scripting language (e.g., Python, KornShell) Preferred Qualifications Experience with big data technologies such as: Hadoop, Hive, Spark, EMR Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. USA, WA, Bellevue - 101,300.00 - 160,000.00 USD annually Company Amazon.com Services LLC Job ID: A10534611

Du willst Ergebnisse, keine Diskussionen? Du arbeitest strukturiert, hast ein klares Verständnis für saubere Prozesse und weißt, wie wichtig Verlässlichkeit im Vertrieb ist? Dann bist du bei uns genau richtig! Wir suchen einen Senior Sales Consultant (m/w/d), der mit klarem Fokus auf Abschlussquote, Systemtreue und messbare Resultate arbeitet. In dieser Position übernimmst du Verantwortung für die direkte Kundengewinnung, führst strukturierte Verkaufsgespräche anhand erprobter Leitfäden und unterstützt beim Ausbau unserer Vertriebsprozesse. Visionen überlassen wir anderen, du bringst Klarheit, Kontrolle und Umsetzung. Deine Aufgaben Kundengewinnung mit Struktur: Gezielte Ansprache potenzieller Kunden, Bedarfsanalyse und Führung durch unseren klar definierten Vertriebsprozess. Pflege stabiler Kundenbeziehungen: Saubere Betreuung mit nachvollziehbaren Abläufen, festen Schritten und dokumentierten Follow-ups. Vertriebsprozesse umsetzen: Einhaltung von Standards, Arbeit mit KPIs und Sicherstellung, dass kein Schritt ausgelassen wird. Teamverantwortung übernehmen: Enge Zusammenarbeit mit dem Team, klare Übergaben und Orientierung durch feste Strukturen. Was wir dir bieten Stabilität & Klarheit: Strukturierte Prozesse, feste Zuständigkeiten und ein durchdachtes Vertriebssystem. Arbeitsplatz mit Planbarkeit: Geregelte Abläufe, messbare Ergebnisse und ein klarer Erwartungshorizont. Modernes Büro in Freiburg: Konzentrationsfördernde Umgebung mit klarer Aufgabentrennung und ruhiger Atmosphäre. Strukturiertes Onboarding: Systematische Einarbeitung, Schritt für Schritt. Teamorientierte Umsetzung: Jeder kennt seinen Bereich, alles greift ineinander, ohne Reibungsverluste. Mehrjährige Vertriebserfahrung, idealerweise im Beratungs- oder Agenturumfeld. Freude an Zielen, Zahlen und dem sichtbaren Erfolg von klaren Abläufen. Unternehmerisches Denken, strukturierte Umsetzung und eigenverantwortliches Handeln. Klare Kommunikation in Deutsch und Englisch, sachlich, effizient, ohne Umwege. Führung mit Struktur, nicht mit Vision, sondern mit System. Find more English Speaking Jobs in Germany on Arbeitnow

Location: Raleigh, and Dallas At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY is the only professional services firm with a separate business unit ("FSO") that is dedicated to the financial services marketplace. Our FSO teams have been at the forefront of every event that has reshaped and redefined the financial services industry. If you have a passion for rallying together to solve the most complex challenges in the financial services industry, come join our dynamic FSO team! We help our clients transform. Together we are changing the way they interact with their Customers, Employees and Partners alike. We are modernizing their applications, creating new ones and driving business efficiency across their ever-changing platform and channel infrastructures. Everything we do centers around this simple story. The opportunity As an FSO Technology Service Delivery Manager, you'll be based in our Service Delivery Center, which is made up of high-performing US-based colleagues who work closely with our experienced advisory professionals. We deliver Technology project-based work and managed services to our clients. Here, you'll work as part of a project team and will be responsible for the design, build/configuration, testing, analysis, delivery and support of Technology solutions. This position is fast-paced and ever-changing, which means you'll need to be a flexible self-starter and be able to manage changing priorities and learning new and rapidly changing technology solutions. We are looking for Frontend Engineers who will collaborate with clients to transform their business through disruptive innovation and transformational design solutions. The team supports clients in modernizing customer-facing systems, processes, and products to deliver intuitive, responsive, accessible, and high-performing digital experiences. The team leverages Angular, React, TypeScript, API integration, cloud technologies, and modern UI engineering practices to enable scalable end-to-end solutions. Your Key Responsibilities The goal is to help our clients solve business problems through frontend engineering solutions. You will work with engagement teams to analyze business and user experience requirements, develop and test responsive web applications, integrate frontend solutions with backend services, and support production deployments. You will contribute to delivering high-quality systems with a focus on usability, accessibility, performance, reliability, and customer experience while continuing to build your technical capabilities and domain knowledge. Skills And Attributes For Success Prior frontend software product development experience, with strong knowledge of modern UI engineering practices and a preferred understanding of DevOps tools and services. Developing engineering solutions through all phases of the project lifecycle, including requirements definition, engineering design, development, integration, and testing; based on a proven agile methodology. Demonstrate hands-on technical capabilities in Angular, React, TypeScript, JavaScript, HTML5, CSS3, and responsive web development. Effectively work with client engagement teams with diverse skills and backgrounds fostering an innovative and inclusive work environment. Demonstrate understanding of current technology environment and industry trends and provide recommendations for engagement and client service issues. Willingness and ability to travel up to 30% of the time. To qualify for the role you must have: Bachelor's degree in computer science or other related field A minimum of 3 years' experience in technology software development Strong frontend development experience using Angular, React, TypeScript, JavaScript, HTML5, CSS3, and modern responsive design practices. Hands-on experience building reusable components, single-page applications, state management solutions, and accessible user interfaces. Experience integrating frontend applications with RESTful APIs and handling authentication, authorization, error handling, and asynchronous data flows. Experience with frontend architecture, micro frontends, performance optimization, browser compatibility, and secure coding practices. Experience with modern collaborative development tools and practices, including Git, npm or Yarn, code reviews, and CI/CD pipelines. Experience with frontend testing frameworks and tools for unit, component, and end-to-end testing, with knowledge of TDD or BDD techniques. Comfortable working in Agile delivery teams and collaborating closely with UX designers, backend engineers, product owners, and QA professionals. Ideally, you'll also have: Experience with the following technologies and practices Angular, React, TypeScript, JavaScript, HTML5, and CSS3 State management using NgRx, Redux, Context API, or similar patterns Unit and component testing using Jest, Jasmine, Karma, or React Testing Library End-to-end test automation using Cypress or Playwright Responsive design, web accessibility, cross-browser compatibility, and performance optimization Node.js tooling, npm or Yarn, Webpack or Vite, cloud platforms, and micro frontend architecture Cloud technologies like AWS, or Azure What We Look For We're interested in intellectually curious people with a passion for finding new and innovative ways to make things better. You'll also need to be a self-starter and quick learner with a strong background in computer science from both theoretical and practical points of view. If you're ready to be the future of the group and make your mark in a growing business, this role is for you. What We Offer You At EY, we harness our collective strength to empower you to shape your future with confidence through professional growth, personal fulfillment and an inclusive culture. Learn more at ey.com/us/careers. The salary range for this job is: New York City, Boston, and Washington DC Metro Areas, Washington State, and Southern California offices – $80,300 to $149,100 Bay Area California offices – $83,700 to $155,300 All other offices locations in the US, including Sacramento – $67,000 to $136,800 Individual salaries within these ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Are you ready to shape your future with confidence? Apply today. To make the most of your application experience, please limit yourself to two applications within a six-month period. EY accepts applications for this position on an on-going basis. For those living in California, please click here for additional information. At EY, our values set the foundation for how we work and the behaviors we expect of our people. Any misrepresentation or falsification of information or lack of integrity at any point in the recruiting process may result in withdrawal of your candidacy, revocation of an offer or immediate termination of employment. EY | Building a better working world EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories. All in to shape the future with confidence. EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, genetic information, national origin, protected veteran status, disability status, or any other legally protected basis, including arrest and conviction records, in accordance with applicable law. EY is committed to providing reasonable accommodation to qualified individuals with disabilities including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, select Option 2 for candidate related inquiries, then select Option 1 for candidate queries and finally select Option 2 for candidates with an inquiry which will route you to EY's Talent Shared Services Team (TSS) or email the TSS at ssc.customersupport@ey.com.