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About The Role The role owns the infrastructure and pipelines that turn ML experiments into reliable, production-grade systems. This covers CI/CD for models, distributed training infrastructure, feature stores, model serving, and observability - the plumbing that determines whether an ML organization ships weekly or stalls in notebook limbo. The position sits at the intersection of platform engineering and machine learning. The MLOps Engineer will work directly with ML engineers and data scientists to make training, deployment, and monitoring fast, reproducible, and boring in the best possible way. Key Responsibilities Design and maintain CI/CD pipelines for ML workflows (GitLab CI, GitHub Actions, or Argo Workflows) covering training jobs, model evaluation gates, and automated deployments Build and operate model serving infrastructure using Kubernetes, KServe/Seldon, or cloud-native endpoints (SageMaker, Vertex AI), with autoscaling and canary rollout strategies Implement experiment tracking and model registry workflows using MLflow or Weights & Biases, ensuring full lineage from data to deployed artifact Build monitoring and observability for production models: drift detection, latency/throughput dashboards, and automated alerting with Grafana, Prometheus, or Datadog Optimize training pipelines for cost and speed - distributed training with PyTorch DDP or Ray, GPU utilization tuning, and spot-instance strategies on AWS or GCP Automate infrastructure as code with Terraform; own Kubernetes manifests, Helm charts, and environment parity across dev/staging/production Partner with data scientists to productionize feature pipelines, leveraging a feature store (Feast, Tecton, or custom) and streaming data with Kafka where appropriate What We Are Looking For 3–6 years of experience in MLOps, platform engineering, or DevOps with significant ML workloads in production Strong Python and scripting skills; solid software engineering fundamentals including testing and code review discipline Deep hands-on experience with Kubernetes and Docker, including running GPU workloads in production Experience with at least one major ML platform: AWS SageMaker, GCP Vertex AI, or Azure ML, plus familiarity with MLflow or W&B Practical knowledge of IaC (Terraform) and cloud networking fundamentals on AWS or GCP Bachelor's degree in Computer Science, Engineering, or equivalent practical experience; track record of owning production infrastructure end-to-end Bonus: experience with LLM serving stacks (vLLM, Triton, TensorRT-LLM), feature stores (Feast, Tecton), Ray, or exposure to SOC 2 / compliance requirements for ML systems

About The Role The role owns the infrastructure that makes ML work in production: training pipelines, model serving, monitoring, and the CI/CD systems that take models from notebook to reliable, scalable deployment. The team partners closely with ML engineers and data scientists to eliminate friction between experimentation and production — building the automated pipelines, observability, and infrastructure standards that let models ship fast and stay reliable. Key Responsibilities Design and maintain end-to-end ML pipelines for training, validation, and deployment using tools like Kubeflow, MLflow, or Airflow Build and scale model serving infrastructure with Docker, Kubernetes, and frameworks like KServe, Seldon, or Triton, supporting both batch and low-latency inference Implement CI/CD for ML systems — automated testing, model versioning, canary deployments, and rollback strategies Establish monitoring and observability for production models: data drift detection, latency/throughput dashboards, and automated alerting with Prometheus and Grafana Manage GPU compute and cloud resources across AWS, GCP, or Azure, optimizing cost and utilization for training and inference workloads Collaborate with data scientists to productionize models, translating experimental code into robust, tested engineering systems Drive platform reliability standards: SLOs, incident response, and postmortems for ML serving infrastructure What We Are Looking For 3–6 years of experience in MLOps, ML engineering, or backend/platform engineering with production ML systems Strong Python skills plus hands-on experience with containerization and orchestration (Docker, Kubernetes) Experience with at least one ML pipeline/workflow tool: Kubeflow, MLflow, Airflow, or SageMaker Pipelines Proficiency with cloud infrastructure (AWS, GCP, or Azure), including GPU instance management and IaC tools like Terraform Practical experience with model serving and monitoring in production, including drift detection and performance tuning Bachelor's degree in Computer Science, Engineering, or equivalent practical experience Bonus: Experience with LLM inference infrastructure (vLLM, TensorRT-LLM, Triton), feature stores (Feast, Tecton), or streaming data systems (Kafka, Flink)

The Position A healthier future. It's what drives us to innovate. To continuously advance science and ensure everyone has access to the healthcare they need today and for generations to come. Creating a world where we all have more time with the people we love. That's what makes us Roche. Advances in AI, data, and computational sciences are transforming drug discovery and development. Roche's Research and Early Development organisations at Genentech (gRED) and Pharma (pRED) have demonstrated how these technologies accelerate R&D, leveraging data and novel computational models to drive impact. Seamless data sharing and access to models across gRED and pRED are essential to maximising these opportunities. The new Computational Sciences Center of Excellence (CoE) is a strategic, unified group whose goal is to harness this transformative power of data and Artificial Intelligence (AI) to assist our scientists in both pRED and gRED to deliver more innovative and transformative medicines for patients worldwide. The Opportunity At Roche's AI for Drug Discovery (AIDD) group (Prescient Design), we are revolutionizing drug discovery with cutting-edge machine learning techniques. We are seeking a highly motivated and skilled ML Infrastructure DevOps Engineer to join our growing team within Genentech Research and Early Development AI Drug Development (gRED AIDD). This role is crucial for building and maintaining the scalable and robust infrastructure that powers our machine learning initiatives. The ideal candidate will be proactive, user-facing, and possess a "get-it-done" attitude, while consistently adhering to corporate standards and best practices. What You'll Do Machine Learning Engineer - DevOps Design, implement, and maintain scalable and reliable ML infrastructure on AWS. Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm. Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment. Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions. Troubleshoot and resolve infrastructure-related issues in a timely manner. Implement and enforce security best practices for ML infrastructure. Document infrastructure designs, processes, and operational procedures. Contribute to initiatives independently as part of a team, delivering assigned outputs. Proactively identify issues and gaps, proposing ideas and suggestions for improvements. Senior Machine Learning Engineer - DevOps Lead the architecture and delivery of significant technical solutions Mentor junior engineers and drive technical alignment and influence across teams Design, implement, and maintain scalable and reliable ML infrastructure on AWS. Demonstrated ability to lead technical projects from conception to completion and deliver high-quality, scalable, and reliable software." to "Who you are Automate deployment, monitoring, alerting, and operational tasks using tools like Terraform and Helm. Manage and optimize CI/CD pipelines and Git repositories for ML projects, ensuring efficient version control to support collaboration and deployment. Collaborate closely with ML engineers and data scientists to understand their infrastructure needs and provide solutions. Troubleshoot and resolve infrastructure-related issues in a timely manner. Implement and enforce security best practices for ML infrastructure. Document infrastructure designs, processes, and operational procedures. Contribute to initiatives independently as part of a team, delivering assigned outputs. Proactively identify issues and gaps, proposing ideas and suggestions for improvements. Who You Are Machine Learning Engineer - DevOps BS/MS with 2-3 years of industry experience required Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc. Strong proficiency with Git and Git repository management. Hands-on experience with Terraform for infrastructure provisioning and management. Experience with Helm for deploying and managing applications on Kubernetes. Proficiency in scripting languages (e.g., Python, Bash) for automation. Excellent problem-solving skills and a strong ability to debug complex issues. Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions. Demonstrated ability to take initiative, anticipate needs, and drive projects to completion. Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines. Ability to write clean code with little syntax/convention feedback. Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD). Familiarity with modern machine learning methods. Knowledge of and experience with high-performance computing, distributed systems, and cloud computing. Senior Machine Learning Engineer - DevOps BS/MS with 3-5 years of industry experience required Proven experience in designing, deploying, and managing infrastructure on Amazon Web Services (AWS), including services such as EC2, S3, RDS, EKS, SageMaker, etc. Strong proficiency with Git and Git repository management. Hands-on experience with Terraform for infrastructure provisioning and management. Experience with Helm for deploying and managing applications on Kubernetes. Proficiency in scripting languages (e.g., Python, Bash) for automation. Excellent problem-solving skills and a strong ability to debug complex issues. Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and user-facing interactions. Demonstrated ability to take initiative, anticipate needs, and drive projects to completion. Ability to thrive in a fast-paced environment and adapt to evolving requirements while adhering to corporate guidelines. Ability to write clean code with little syntax/convention feedback. Applies software engineering best practices (linting automation, unit testing, documentation, CI/CD). Familiarity with modern machine learning methods. Knowledge of and experience with high-performance computing, distributed systems, and cloud computing. Preferred Experience with MLOps platforms and tools. Familiarity with CI/CD pipelines for ML workflows. Knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack) Relocation benefits are NOT available for this job posting The expected salary range for this position based on the primary location of California for the Machine Learning Engineer is $147,600, - $274,000 and New York is $141,100 - $262,100, and the Senior Machine Learning Engineer for California is $167,400 - $310,800 and New York is $160,100 - $297,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below. Benefits #ComputationCoE #tech4lifeComputationalScience #tech4lifeAI Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

About SimpliSafe We're a high-tech home security company that's passionate about protecting the life you've built and our mission of keeping Every Home Secure. And we've created a culture here that cares just as deeply about the career you're building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We don't just want you to work here. We want you to grow and thrive here. We're embracing a hybrid work model that enables our teams to split their time between office and home. Hybrid for us means we expect our teams to come together in our state-of-the-art office on two core days, typically Tuesday, Wednesday, or Thursday – working together in person and choosing where they work for the remainder of the week. We all benefit from flexibility and get to use the best of both worlds to get our work done. Why are we hiring? Well, we're growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure. About the Role We are looking for an experienced ML Infrastructure/MLOps Engineer to join our team as a Senior Machine Learning Engineer. In this role, you will drive the development and deployment of machine learning models, optimize ML workflows, and help ensure our infrastructure is scalable, reliable, and secure. If you have a passion for automation, cloud technology, and delivering high-impact solutions, we'd love to hear from you. Responsibilities: Lead the architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases. Collaborate with data scientists, engineers, and stakeholders to operationalize ML models. Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases. Design, implement, and own comprehensive production monitoring for ML models/systems. Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads. Drive best practices in model versioning, observability, reproducibility, and deployment reliability Serve in an on-call rotation as a first responder for software owned by your team. Qualifications 5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure. Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks. Hands-on experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools (e.g., Terraform, Cloud Formation). Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch). Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring. Strong communication skills for partnering with cross-functional technical and non-technical teams. Nice to Have Experience with Ray for inference, or pipeline orchestration Hands-on experience with deploying large language models (LLMs) to production. Experience with frameworks such as vLLM is a plus. Experience with distributed systems and big data technologies (e.g., Spark, Hadoop). Experience with event-driven or streaming architectures (e.g., Kafka, Kinesis). Knowledge of cloud security, IAM, and compliance best practices for ML workloads. LLM application development, including prompt engineering and evaluation. What Values You'll Share Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them. Aim High - Always challenging ourselves and others to raise the bar. No Ego - Maintaining a "no job too small" attitude, and an open, inclusive and humble style. One Team - Taking a highly collaborative approach to achieving success. Lift As We Climb - Investing in developing others and helping others around us succeed. Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment. What We Offer A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here) Free SimpliSafe system and professional monitoring for your home. Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change. The target annual base pay range for this role is $152,900 - $203,800 This target annual base pay range represents our good-faith estimate of what we expect to pay for this role. We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually. We carefully tailor individual compensation packages, including base pay, taking into consideration employees' job-related skills, experience, qualifications, work location, and other relevant business factors. Beyond base pay, we offer a Total Rewards package that may include participation in our annual bonus program, equity, and other forms of compensation, in addition to a full range of medical, retirement, and lifestyle benefits. More details can be found here. We're committed to fair and equitable pay practices, as well as pay transparency. We regularly review our programs to ensure they remain competitive and aligned with our values. We wholeheartedly embrace and actively seek applications from all individuals, no matter how they identify. We are committed to cultivating a diverse and inclusive workplace, and we believe our work is enriched when we incorporate a multitude of perspectives, backgrounds, and experiences. We want everyone who works here to thrive and contribute to not only our mission of keeping every home secure, but also to making our workplace safe and supportive for others. If a reasonable accommodation may be needed to fully participate in the job application or interview process, to perform the essential functions of a position, or to receive other benefits and privileges of employment, please contact careers@simplisafe.com .

About The Role As a Data and Machine Learning Engineer , you will make an impact by designing, building, and optimizing scalable data platforms and machine learning solutions within a Microsoft Azure environment. You will be a valued member of the Data Engineering team and work collaboratively with data scientists, cloud engineers, architects, and cross-functional stakeholders to deliver secure, reliable, and production-ready solutions. In This Role, You Will Design, develop, and maintain scalable data ingestion, transformation, and ETL/ELT pipelines. Build and optimize Azure-based data platforms using Databricks, Synapse Analytics, Data Lake, and related cloud technologies. Deploy, operationalize, and support machine learning solutions through CI/CD pipelines and MLOps practices. Monitor, troubleshoot, and optimize data and machine learning workloads to ensure performance, reliability, and scalability. Collaborate with engineering and data science teams to translate business and technical requirements into production-ready solutions. Work model At Cognizant, we strive to provide flexibility wherever possible, and we are here to support a healthy work-life balance through our various wellbeing programs. Based on this role's business requirements, this is an onsite position requiring 5 days a week in a client or Cognizant office in Mason, Ohio. The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations. What You Need To Have To Be Considered Proven experience as a Data Engineer, Machine Learning Engineer, or Cloud Platform Engineer. Strong hands-on experience with Microsoft Azure data engineering and analytics services. Proficiency in Python, SQL, and/or Scala. Experience developing, supporting, and optimizing production-grade data pipelines. Hands-on experience with Apache Spark, Databricks, or comparable distributed data processing frameworks. Familiarity with CI/CD, DevOps, and MLOps practices. Ability to independently design, develop, troubleshoot, and deliver technical solutions. Strong communication and collaboration skills with experience working across cross-functional teams. These Will Help You Stand Out Experience with Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake. Knowledge of MLflow, Docker, Kubernetes, or Azure Kubernetes Service (AKS). Experience with Delta Lake, Parquet, and modern cloud data architectures. Familiarity with infrastructure as code, orchestration frameworks, and cloud monitoring tools. Exposure to enterprise data integrations, including SAP Change Data Capture (CDC). Experience working in Agile development environments. We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role. Salary And Other Compensation Applications will be accepted until November 08, 2026 The annual salary for this position is between $ 130,000 - $ 150,000 depending on experience and other qualifications of the successful candidate. This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans. Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements: Medical/Dental/Vision/Life Insurance Paid holidays plus Paid Time Off 401(k) plan and contributions Long-term/Short-term Disability Paid Parental Leave Employee Stock Purchase Plan Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

Archer is collaborating with Bet365 to connect them with exceptional professionals for this role. We are seeking a highly pragmatic, results-driven Machine Learning (ML) Engineer to join our newly established US Data team. In this role, you will build the reliable, automated infrastructure that powers our machine learning lifecycle. Your primary mission is to operationalize and scale the models developed by our data science team, taking them from prototype to robust, production-grade systems with high velocity. You'll focus on building reliable, automated and maintainable systems, keeping solutions pragmatic rather than over-engineered. You will also be passionate about automation, software engineering excellence, and MLOps. You will report to the Data Science Team Leader and work in close alignment with the US AgentOps Team Lead (responsible for agentic and model orchestration platforms) and our UK technical excellence center. You will act as the bridge between model development and reliable platform engineering. Preferred Skills And Experience Proven experience as an ML Engineer, Data Engineer, or Software Engineer with a clear focus on deploying, monitoring, and scaling machine learning systems in production. A pragmatic, proactive approach to system design, prioritizing speed, reliability, and business value over complex, theoretical infrastructure. Strong Python programming skills, with a solid grasp of software engineering patterns, API development, and automated testing frameworks. Extensive hands-on experience with Google Cloud Platform (GCP). Practical experience with Vertex AI (specifically Vertex AI Pipelines, Endpoints, and Workbench). Proficiency with containerization (Docker) and container orchestration tools. Excellent communication skills, with the ability to translate software engineering concepts for data scientists and operational requirements for product leads. Experience utilizing Infrastructure as Code (IaC) tools such as Terraform. Experience running containerized workloads on Google Kubernetes Engine (GKE). Familiarity with real-time streaming tools like Apache Kafka or GCP Pub/Sub. What you will be doing Owning the deployment of machine learning models to production. Build and maintain scalable, low-latency prediction endpoints using GCP Vertex AI. Designing, implementing, and maintaining CI/CD/CT (Continuous Integration, Continuous Delivery, Continuous Training) pipelines for machine learning workflows using Vertex AI Pipelines, Cloud Build, and related GCP tools. Setting up automated monitoring and alerting frameworks (e.g., Vertex AI Model Monitoring) to track data drift, model drift, and system performance in real-time. Championing best practices for software engineering within the Data Science team, including robust unit testing, containerization, version control, and CI/CD automation. Working closely with the Data Science Team Leader, Junior Data Scientists, and the AgentOps Team Lead to accelerate deployment cycles, remove operational bottlenecks, and maintain high deployment velocity.

Why Wells Fargo Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we're a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job – it's about finding all of the elements to help you thrive, in one place. Living the Well Life means you're supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. You'll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. And we're recognized for it – Wells Fargo once again ranked in the top three – making us the #1 financial services employer – on the 2025 LinkedIn Top Companies list of best workplaces "to grow your career" in the U.S. Join us! About This Role Wells Fargo is seeking a Lead AI Workflow Designer & Prompt Architect to design, develop, and optimize AI-powered workflows using large language models (LLMs), AI agents, and orchestration frameworks to solve complex business challenges. This role combines strategic problem framing, prompt engineering, workflow architecture, and technical implementation to deliver scalable, reliable AI solutions aligned with business needs. This individual bridges business objectives and AI execution by translating ambiguous challenges into structured, multi-step workflows that coordinate prompts, tools, context, data, and agent interactions. The role requires strong analytical and technical skills to independently assess system behavior, prototype solutions, troubleshoot workflow issues, and improve AI performance through experimentation and operational insights. In This Role, You Will Partner with business, product, technology, and operations teams to understand business challenges and identify opportunities to leverage AI and agentic solutions. Translate business problems into structured AI workflow designs that break complex tasks into logical stages and execution paths. Design, develop, and optimize multi-step prompt workflows that enable AI agents to perform reasoning, decision support, content generation, analysis, and task execution activities. Define workflow architecture including prompts, context requirements, tool interactions, orchestration logic, handoffs, dependencies, and output requirements. Determine how information, memory, context, and intermediate outputs should be managed throughout workflow execution. Design and maintain prompt libraries, reusable workflow templates, and orchestration patterns that can be leveraged across multiple business use cases. Collaborate with product and engineering teams to integrate AI workflows into enterprise applications and business processes. Analyze workflow execution logs, model outputs, and intermediate agent responses to identify root causes of failures, performance degradation, or inconsistent results. Troubleshoot issues related to prompt design, context management, agent behavior, tool integrations, data pipelines, file structures, APIs, and execution environments. Evaluate workflow effectiveness using qualitative and quantitative measures and implement improvements to increase reliability, accuracy, efficiency, and user outcomes. Improve context engineering strategies to optimize information retrieval, grounding, memory management, and response quality. Develop lightweight automation, scripts, and utilities to support workflow development, experimentation, testing, evaluation, monitoring, and operational efficiency. Perform data inspection, transformation, validation, and analysis activities to support AI workflow development and troubleshooting. Prototype innovative solutions rapidly when existing tools, workflows, or capabilities do not fully address a business need. Contribute to AI governance, risk management, quality assurance, and responsible AI practices by ensuring workflows operate within established standards and controls. Stay informed on emerging AI technologies, agent frameworks, orchestration platforms, prompt engineering techniques, and industry best practices. Required Qualifications 5+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications Experience designing, implementing, and optimizing multi-step LLM, generative AI, and agentic workflows. Strong problem-solving skills with the ability to translate complex business challenges into scalable AI solutions. Expertise in prompt engineering, human-in-the-loop workflows, and AI performance optimization. Ability to troubleshoot and diagnose issues across prompts, agents, context management, integrations, and workflow execution. Proficiency in Python, APIs, JSON, Markdown, and working with structured and unstructured data. Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms. Knowledge of agent orchestration frameworks, multi-agent architectures, and modern workflow orchestration patterns. Understanding of RAG, context engineering, memory management, tool calling, and agent planning methodologies. Experience integrating AI solutions with enterprise applications, automation platforms, cloud AI services, and business processes. Strong communication, collaboration, governance, risk, and responsible AI expertise, including evaluation, monitoring, compliance, and operational controls Job Expectations This position is NOT eligible for Visa sponsorship. Ability to work on site per Wells Fargo's standard operating model in the listed location (hybrid schedule – 3 days on-site & 2 remote). The ability to travel up to 10% of the time. Posting Location: Charlotte, NC Irving, NC Chandler, AZ The Chief Operations Office (COO) functions adhere to a location strategy; therefore, your candidacy may be determined based on your current location. Remote work locations are not available for these roles, so if you are not in a location listed on the posting, you must commit to self-relocation within an agreed upon timeframe. ** Posting End Date 29 Oct 2026 Job posting may come down early due to volume of applicants. We Value Equal Opportunity Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. Applicants With Disabilities To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo. Drug and Alcohol Policy Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more. Wells Fargo Recruitment And Hiring Requirements Third-Party recordings are prohibited unless authorized by Wells Fargo. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process. Reference Number R-579912-1

Who is Authenticx? Authenticx is on a mission to help humans understand humans. Our software platform is the new standard for humanizing customer interaction data at scale. We do this by channeling our passion and talent into helping health care leaders listen to their conversational data in a way that delivers value to the enterprise. What do we offer our team members? A culture based on our core values of Authenticity, Courage and Having Fun A collaborative environment that supports your personal and professional development Hybrid working flexibility Free health insurance options Comprehensive benefits - medical, vision, dental, life, and disability insurance HSA and FSA plans 401(K) Unlimited vacation time Generous paid holidays, sick leave, and parental leave Perks at Work membership for discounts on shopping, travel and much more Position Summary The AI Prompt Engineer will lead the design, development, and optimization of large language model (LLM) prompts used for scalable conversation scoring at Authenticx. This role is critical in translating objective scoring rubrics into reusable, testable prompt logic that supports our enterprise healthcare clients. The engineer will collaborate across teams including engineering, implementation, product, and data labeling to deliver reliable and high-quality prompt workflows. This is a hands-on role suited for someone who thrives in an experimental, iterative environment and has an interest in scaling natural language solutions. Key Responsibilities Design and implement sophisticated LLM prompts aligned to internal scoring rubrics and customer-specific needs. Conduct prompt testing and evaluation using labeled datasets to ensure performance accuracy. Collaborate with engineering to improve tooling and infrastructure for managing LLM scoring workflows. Maintain a centralized prompt library to ensure reuse and standardization across use cases. Document prompt strategies, testing approaches, and outcomes for internal learning. Identify and resolve inefficiencies in the prompt development and deployment process. Partner with product and data labeling teams to improve the quality and consistency of scoring outputs. Required Qualifications Strong understanding of LLMs, NLP systems, and prompt engineering concepts. Ability to structure and document complex logic in a scalable and repeatable manner. Demonstrated ability to collaborate effectively with both technical and non-technical teams. Analytical mindset with an interest in experimentation, iteration, and data-driven decision-making. Preferred Qualifications Experience in structured data labeling or QA workflows. Familiarity with tools like LangChain, OpenAI/GPT APIs, or vector databases. Background in linguistics, cognitive science, or HCI. Proficiency in Python or scripting tools for evaluation or automation. Additional Information May include occasional travel for team meetings or planning sessions Must be authorized to work in the U.S. without current or future visa sponsorship. This role will be hybrid based out of our Indianapolis office,

Entry Level Job Description We are seeking a Generative AI Engineer to build AI-powered applications using large language models and generative AI technologies. Responsibilities Develop GenAI applications and chatbots Work with LLM APIs Implement prompt engineering techniques Build retrieval-augmented generation (RAG) systems Requirements Strong Python programming skills Knowledge of LLMs and generative AI concepts Familiarity with OpenAI API and LangChain Understanding of vector databases

Department Customer CARE Our Company Promise We are committed to provide our Employees a stable work environment with equal opportunity for learning and personal growth. Creativity and innovation are encouraged for improving the effectiveness of Southwest Airlines. Above all, Employees will be provided the same concern, respect, and caring attitude within the organization that they are expected to share externally with every Southwest Customer. Job Description As a CARE AI Prompt Design Consultant, you'll help shape the AI-powered experiences that connect Southwest's Customer-first values with the tools Customers and Employees use every day. You'll lead prompt strategy, design, testing, and continuous improvement across voice, chat, email, and digital servicing channels, helping ensure AI-generated responses are accurate, clear, helpful, and aligned with Southwest policies and service standards. Partnering closely with frontline Teams, Customer CARE Operations, Digital, Customer Experience, Commercial, Quality, Knowledge Management, Technology, and AI product Teams, you'll translate real-world servicing needs into effective prompts, guardrails, testing practices, and scalable governance. You'll use performance data and feedback to strengthen response quality, simplify complex interactions, and help Employees use AI-enabled tools responsibly and confidently. Your work will help Southwest innovate thoughtfully while creating more consistent experiences and delivering the Hospitality our Customers count on. Additional Details The culture of Southwest Airlines means we value the camaraderie, collaboration, and innovation that occurs when we come together and interact face-to-face at our vibrant Corporate Campus. Due to the nature of this role, you would be required to work from our Dallas, TX Headquarters facility during business hours. U.S. citizenship or current authorization to work in the U.S. required and no current or future work authorization sponsorship available. We're committed to fair hiring practices and to making employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, age, military or veteran status, disability, genetic information, or other legally protected characteristics. Responsibilities Lead prompt strategy, design, testing, optimization, and ongoing management for Customer CARE AI experiences across voice, chat, email, and digital servicing channels to improve clarity, accuracy, containment, self-service success, Representative confidence, and the overall Customer experience Design, document, and maintain prompt libraries, reusable frameworks, response patterns, and channel-specific standards Establish prompt governance, change control, quality criteria, testing protocols, and review cadences that support responsible AI use Partner with Customer CARE Operations, Digital, Customer Experience, Commercial, Quality, Knowledge Management, Technology, and AI product teams to align prompts with policies, procedures, experience design requirements, Customer needs, and Representative workflows Evaluate AI-generated responses for accuracy, completeness, clarity, tone, brand alignment, policy compliance, escalation appropriateness, and usefulness to Customers and Representatives Analyze AI performance data, quality reviews, Customer feedback, Representative feedback, and operational outcomes to identify prompt improvement opportunities Lead scenario testing, A/B testing, and regression testing to improve AI response quality, consistency, and reliability Translate business needs, servicing policies, disruption procedures, and Customer scenarios into prompt structures, grounding requirements, guardrails, knowledge retrieval behavior, and escalation logic Develop documentation, reporting, recommendations, training, and change support that help Leaders and Employees use AI-enabled tools effectively and responsibly Monitor emerging AI capabilities, prompt engineering techniques, and conversational design practices to identify innovation opportunities while maintaining quality, consistency, compliance, and Southwest's Customer-first service standards May perform other job duties as directed by Employee's Leaders Knowledge, Skills And Abilities Advanced knowledge of prompt engineering principles, conversational design methods, generative AI capabilities, and AI response optimization practices Advanced knowledge of Customer CARE operations, contact center environments, Customer servicing procedures, and Customer experience expectations Knowledge of large language model behavior, grounding, retrieval, response guardrails, prompt testing, and iterative optimization methods Skilled in designing and refining prompts that produce accurate, relevant, clear, and consistent AI-generated responses Skilled in evaluating AI-generated content for quality, usefulness, tone, brand alignment, policy compliance, and escalation appropriateness Skilled in translating complex policies, Customer scenarios, disruption procedures, and Representative workflows into structured prompt and conversational requirements Skilled in analyzing performance metrics, quality insights, Customer and Representative feedback, and operational data to identify improvement opportunities Skilled in documenting prompt standards, test plans, decision logic, prompt libraries, governance processes, and recommendations Ability to communicate AI concepts, risks, and recommendations to technical and non-technical audiences Ability to balance Customer and Employee experience objectives, operational requirements, compliance considerations, and business priorities while building alignment across business and Technology teams Education Required: High School Diploma or GED Experience Advanced level experience, seasoned and specialized knowledge in: Prompt engineering, conversational AI, generative AI, or AI-enabled Customer experience design Customer CARE, contact center operations, Customer service, or Customer experience management Testing, quality evaluation, optimization, and continuous improvement of AI-enabled experiences Customer-facing or Employee-facing digital servicing tools across voice, chat, email, or related channels Knowledge management, conversational design, content strategy, or Customer communication standards Cross-functional consultation, governance, documentation, training, or scalable operating models Preferred: Experience with Salesforce Preferred: Experience with Amazon Web Services Connect Licensing/Certification N/A Physical Abilities Ability to perform work duties from limited space workstation/desk/office area for extended periods of time Ability to communicate and interact with others in the English language to meet the demands of the job Ability to use a computer and other office productivity tools with sufficient speed and accuracy to meet the demands of the job Other Qualifications Must maintain a well-groomed appearance per Company appearance standards as described in established guidelines Must be a U.S. citizen or have authorization to work in the United States as defined by the Immigration Reform Act of 1986 Must be at least 18 years of age Must be able to comply with Company attendance standards as described in established guidelines Pay & Benefits Competitive market salary from $119,900 per year to $133,200 per year depending on qualifications and experience. For eligible Leadership and individual contributor roles, additional bonus opportunities are available and awarded at the discretion of the Company. Benefits you'll love Fly for free, as a privilege, on any open seat on all Southwest flights (your eligible dependents too) Southwest will help fund your Retirement Savings Plan, which includes a dollar-for-dollar 401(k) Company match contribution of up to 9.3% of your eligible earnings Potential for annual profit-sharing contribution in the Southwest Retirement Savings Plan—when Southwest profits, you profit** Competitive health insurance for you and your eligible dependents Southwest offers health plan coverage options that start from the very first day of employment. You'll have 30 days to select and enroll in your health plan, and coverage will be retroactively available to your first day of employment. Explore more benefits you'll love: https://careers.southwestair.com/benefits Pay amount doesn't guarantee employment for any particular period. 401(k) Company match contributions are subject to the plan's vesting schedule. Match contributions may vary based on the position. Profit-sharing contributions are subject to the Retirement Savings Plan vesting schedule and are made at the discretion of the Company. Southwest Airlines is an Equal Opportunity Employer. Please print/save this job description because it won't be available after you apply. Job Posting End Date 10/29/2026

Prompt Engineer – Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Prompt Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $76,000–$99,000 Annually Experience Required: 8+ years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary We are looking for a Prompt Engineer to define and lead the strategy, patterns, and tooling for designing prompts, agentic workflows, and LLM-based application architectures across the organization. The role combines deep practical mastery of modern LLMs with the discipline of building reusable design patterns, evaluation frameworks, and developer tooling that scale across many teams and use cases. The ideal candidate has shipped LLM-powered products in production, is fluent in prompt design patterns and agent architectures, and brings strong judgment about when and how to apply different LLM techniques responsibly. Required Qualifications Bachelor's or Master's degree in Computer Science, Computational Linguistics, or a related field Six or more years of software engineering experience, with significant time on LLM-based applications Demonstrated experience shipping LLM-powered products to production Deep familiarity with modern LLM APIs and agent frameworks Strong understanding of retrieval-augmented generation, embeddings, and vector databases Experience designing evaluation pipelines for non-deterministic systems Strong Python skills and comfort with modern application frameworks Solid grasp of responsible AI principles, including safety and policy considerations Excellent written and verbal communication skills Track record of mentoring engineers and influencing technical direction Preferred Qualifications Public writing, talks, or open-source contributions on LLM application development Experience with multi-agent architectures and complex tool-use systems Familiarity with fine-tuning workflows and when to choose them over prompting Exposure to product domains such as customer support, coding assistants, or analytics agents Experience integrating LLMs into enterprise software systems with strict compliance requirements How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to hilda@bvteck.com. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. Any improper interference with employees' ability to perform their job duties may result in disciplinary action up to and including termination of employment. Powered by JazzHR dvGsD8rNNK

Why Wells Fargo Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we're a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job – it's about finding all of the elements to help you thrive, in one place. Living the Well Life means you're supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. You'll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. And we're recognized for it – Wells Fargo once again ranked in the top three – making us the #1 financial services employer – on the 2025 LinkedIn Top Companies list of best workplaces "to grow your career" in the U.S. Join us! About This Role Wells Fargo is seeking a Lead AI Workflow Designer & Prompt Architect to design, develop, and optimize AI-powered workflows using large language models (LLMs), AI agents, and orchestration frameworks to solve complex business challenges. This role combines strategic problem framing, prompt engineering, workflow architecture, and technical implementation to deliver scalable, reliable AI solutions aligned with business needs. This individual bridges business objectives and AI execution by translating ambiguous challenges into structured, multi-step workflows that coordinate prompts, tools, context, data, and agent interactions. The role requires strong analytical and technical skills to independently assess system behavior, prototype solutions, troubleshoot workflow issues, and improve AI performance through experimentation and operational insights. In This Role, You Will Partner with business, product, technology, and operations teams to understand business challenges and identify opportunities to leverage AI and agentic solutions. Translate business problems into structured AI workflow designs that break complex tasks into logical stages and execution paths. Design, develop, and optimize multi-step prompt workflows that enable AI agents to perform reasoning, decision support, content generation, analysis, and task execution activities. Define workflow architecture including prompts, context requirements, tool interactions, orchestration logic, handoffs, dependencies, and output requirements. Determine how information, memory, context, and intermediate outputs should be managed throughout workflow execution. Design and maintain prompt libraries, reusable workflow templates, and orchestration patterns that can be leveraged across multiple business use cases. Collaborate with product and engineering teams to integrate AI workflows into enterprise applications and business processes. Analyze workflow execution logs, model outputs, and intermediate agent responses to identify root causes of failures, performance degradation, or inconsistent results. Troubleshoot issues related to prompt design, context management, agent behavior, tool integrations, data pipelines, file structures, APIs, and execution environments. Evaluate workflow effectiveness using qualitative and quantitative measures and implement improvements to increase reliability, accuracy, efficiency, and user outcomes. Improve context engineering strategies to optimize information retrieval, grounding, memory management, and response quality. Develop lightweight automation, scripts, and utilities to support workflow development, experimentation, testing, evaluation, monitoring, and operational efficiency. Perform data inspection, transformation, validation, and analysis activities to support AI workflow development and troubleshooting. Prototype innovative solutions rapidly when existing tools, workflows, or capabilities do not fully address a business need. Contribute to AI governance, risk management, quality assurance, and responsible AI practices by ensuring workflows operate within established standards and controls. Stay informed on emerging AI technologies, agent frameworks, orchestration platforms, prompt engineering techniques, and industry best practices. Required Qualifications 5+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications Experience designing, implementing, and optimizing multi-step LLM, generative AI, and agentic workflows. Strong problem-solving skills with the ability to translate complex business challenges into scalable AI solutions. Expertise in prompt engineering, human-in-the-loop workflows, and AI performance optimization. Ability to troubleshoot and diagnose issues across prompts, agents, context management, integrations, and workflow execution. Proficiency in Python, APIs, JSON, Markdown, and working with structured and unstructured data. Experience using AI-assisted development tools such as GitHub Copilot, Claude Code, Cursor, or similar platforms. Knowledge of agent orchestration frameworks, multi-agent architectures, and modern workflow orchestration patterns. Understanding of RAG, context engineering, memory management, tool calling, and agent planning methodologies. Experience integrating AI solutions with enterprise applications, automation platforms, cloud AI services, and business processes. Strong communication, collaboration, governance, risk, and responsible AI expertise, including evaluation, monitoring, compliance, and operational controls Job Expectations This position is NOT eligible for Visa sponsorship. Ability to work on site per Wells Fargo's standard operating model in the listed location (hybrid schedule – 3 days on-site & 2 remote). The ability to travel up to 10% of the time. Posting Location: Charlotte, NC Irving, NC Chandler, AZ The Chief Operations Office (COO) functions adhere to a location strategy; therefore, your candidacy may be determined based on your current location. Remote work locations are not available for these roles, so if you are not in a location listed on the posting, you must commit to self-relocation within an agreed upon timeframe. ** Posting End Date 29 Oct 2026 Job posting may come down early due to volume of applicants. We Value Equal Opportunity Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic. Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements. Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process. Applicants With Disabilities To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo. Drug and Alcohol Policy Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more. Wells Fargo Recruitment And Hiring Requirements Third-Party recordings are prohibited unless authorized by Wells Fargo. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process. Reference Number R-579912-2