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Ready to Take on a New Challenge in Enterprise Sales? Are you a driven, energetic sales professional looking for your next big adventure? Do you thrive on taking ownership, unlocking strategic accounts, and closing complex, high-value deals in a fast-paced environment? Are you excited by cutting-edge technology in a dynamic industry, and motivated by the opportunity to make a measurable impact; not just on your career, but on the world? If so, we want to hear from you. Where You'll Make an Impact: As an Enterprise Account Executive, you'll join our high-performing EMEA sales team, reporting to the Regional Sales Manager and VP EMEA. You'll take full ownership of your territory and become a trusted advisor to stakeholders across the Crypto and Financial Services landscape. You're not just here to sell, you're here to transform how leading enterprises combat crypto crime with Elliptic's industry-leading compliance and investigation solutions. You'll gain deep product expertise and apply your understanding of evolving global and regional regulations to build compelling business cases that speak directly to our customers' pain points. This is an exciting opportunity for someone looking for a role where you can make an impact not just on the company you work for but also on the market you work in. Fascinating and challenging work is the norm - working at Elliptic is never boring! What you will do: Run the full enterprise sales cycle, from pipeline generation to deal closure, across a territory with massive potential and that has considerable inbound interest. Proactively identify, engage, and convert strategic enterprise accounts (including pre-defined targets and new prospects). Develop and execute multi-threaded sales strategies to engage diverse stakeholders (compliance, legal, risk, procurement, tech, C-level). Handle 5-, 6- and 7-figure deal cycles with skill, creativity, and precision leveraging persuasion, influence, and value based selling techniques. Drive account expansion through timely up-sell and cross-sell opportunities, maximizing value delivered to our customers. Partner with global peers to collaborate on multi-region and strategic global accounts with long-term growth potential. Collaborate with internal sales engineers, product experts, customer success, and marketing, as well as partner channels, to expand your reach and velocity. Stay ahead of industry shifts and translate emerging challenges into opportunities for Elliptic's solution suite. Represent Elliptic at key industry events and conferences to strengthen relationships and identify new prospects. Be an ambassador of the Elliptic brand, living our values of curiosity, trust, and action in every interaction. What you will achieve in the first 6 months: Completed Elliptic's product certifications and onboarding processes. Mapped your territory, identified your top 20 target accounts, and built a qualified pipeline of at least 3x your quarterly quota through a combination of inbound, outbound, and partner-sourced opportunities. Identified upsell or cross-sell motion in an existing Elliptic account in your territory and have it actively in play to build a qualified pipeline of at least 2x of your quarterly quota through proactive whitespace mapping and engagement in collaboration with the Customer Success Managers. Run complete discovery cycles with at least 10 enterprise prospects, using the Value Pyramid to connect client pain points to our solutions, applying MEDDPPICC to qualify or disqualify with confidence, and have a clear view of what you're walking away from and why. Progressed at least 2 opportunities to late-stage negotiation and closed your first deal, demonstrating you can manage the full enterprise cycle from initial engagement through legal and procurement. Built multi-threaded relationships across your strategic accounts - compliance, risk, and C-suite - not just a single champion per account. Earned a reputation internally with your SE, CS, marketing, and partner team as a well-prepared, collaborative account owner who closes the loop and uses internal resources without wasting them. You will be a great fit here if you are: A driven, tenacious "hunter" who thrives on owning their number and finding creative ways to exceed it. Experienced in B2B enterprise SaaS and/or DaaS sales within RegTech, FinTech, and/or Crypto. A proven track record of consistently closing successful enterprise deals across multiple years and companies. Comfortable leading complex, long-cycle and large deals involving multiple stakeholders, but also agile enough to take on quick-close 5-figure deals. Commercially curious, you ask smart questions, seek to understand the "why" behind a customer's problems, and use those insights to tailor impactful solutions. Confident, consultative, and persuasive, able to build strong stakeholder relationships at all levels, from mid-level managers to C-suites. A collaborative team player, independent yet never a "lone wolf." You value and engage support from your pack. Agile, resourceful, and fearless, you see opportunity where others see blockers and know how to create inroads where none appear to exist. Willingness to travel to customers and industry events and conduct business face to face. Our ideal candidate has: Excellent oral and written communication skills and the ability to establish meaningful relationships with C-suite and executive stakeholders. Technical acumen with the ability to establish credibility with technical decision makers. Driven and solutions-oriented: you know how to navigate roadblocks and keep deals moving forward. Familiarity with the MEDDPPICC methodology and Value Based Selling. Proficiency in CRM systems (HubSpot or similar), LLMs and other AI-driven prospecting and work efficiency tools. Passionate about generative AI and excited to help customers navigate a rapidly evolving industry. Bonus Points for: An existing network of connections across the Banking, Financial Services, and Insurance (BFSI) space. Fluency in French, German, Spanish, or Italian. A proven use case and understanding of agentic AI is a strong plus. Ultimately we are looking to hire those who want to be the future leaders in the industry, super intrigued by Crypto and have an awesome mindset to learn so if you don't meet all the criteria still do apply! Benefits: Competitive salary Share Options Holiday - 25 days Private Health Insurance Collaborative, flexible and friendly environment: We understand that flexibility is the key to maintaining a healthy work-life balance. Social events, which include regular team lunch on us, quarterly full day events and an annual company 3-day event - this year these are taking place virtually Personal training budget & LinkedIn Learning subscription We know Diversity and Inclusion is much deeper than just hiring, but it's important for us to mention it here. We welcome and embrace individuals of all backgrounds and identities at Elliptic, and this is an ongoing priority for us. We know incredible people don't all think in the same way. We want to be challenged every day. We believe our diverse team of individuals underpins this by bringing creative thinking and innovation to Elliptic every day. We are committed to creating a diverse, inclusive and equitable workplace, so we welcome applications from everyone, even if you may not think you fit all of the requirements of our roles. We foster an environment of psychological safety, where everyone feels comfortable to bring their whole self to work. Find Jobs in Germany on Arbeitnow

Company Overview We are a full-service EPCM committed to delivering innovative solutions across various industries. Our team is dedicated to excellence, ensuring that every project meets the highest standards of quality and efficiency. We are currently seeking an Electrical Engineering Project Manager to join our team. Role The Electrical Engineering Project Manager (PM) is responsible for leading the delivery of projects for clients ? including project scope, cost, quality, and schedule through to the completion of the project. The PM works closely with the Project team, and will manage project risks, ensure project safety, and maintain a positive relationship with clients. A successful Project Manager works effectively as a team leader and adapts to various situations quickly while maintaining the highest level of professionalism. They possess strong troubleshooting abilities and formulate / coordinate comprehensive strategies for resolving technical and project challenges. Areas of Accountability The Electrical Project Manager will be responsible for Project delivery and execution; duties include: Manage the full Project lifecycle from initiation to closeout. Support estimate development including discipline-specific input into the estimate. Lead Project planning, design and execution activities, schedules, budgets, and resources. Responsible for assembling the Project team (including design, procurement, HSS&E, Project Controls, quality management). Manage multiple projects simultaneously, ensuring they are completed on time, within budget, and to the required quality and safety standards. Develop and maintain positive relationships with clients, contractors, and team members, and provide regular Project status updates to stakeholders. Monitor and report on Project progress, identifying and resolving issues and risks as they arise. Manage Project documentation, including contracts, change orders, and project reports. Coordinate with other departments and stakeholders to ensure Project success. May provide technical guidance to Designers and Senior Engineers. Share lessons learned, risks, and opportunities with other team members. Make decisions and recommendations within established guidelines, procedures, or policies. Manage the turn-over of deliverables and Project closeout activities. Ensure that comprehensive environmental and safety standards are in place and being followed. Active participation in discipline specific HAZOP/HAZID/3D Model Reviews. Qualification Requirements The ideal candidate will possess: Location: This is an in-office role based in Calgary, AB. Candidates must reside in the Calgary area or be willing to relocate. Education: Bachelor?s degree in Electrical Engineering (ideal; other engineering disciplines may be considered) Certifications: Alberta registration as P.Eng. is preferred; PMP certification is an asset. Experience: Minimum of 4 years in engineering, project engineering or project management, with a strong focus on managing multiple, concurrent projects ranging in scope from $1M-$50M TIC or $50,000 - $500,000 in engineering services. Industry Knowledge: Familiarity with industrial/facilities engineering: process systems, piping, equipment installation, power distribution, PLC/DCS/SCADA systems, commissioning practices, and construction methodologies is preferred. Technical Expertise: Solid understanding of mechanical or EIC engineering principles, including design and construction processes. Project Management Skills: Ability to manage 10-15 small projects at a time, with effective prioritization and organizational skills. Site Travel: Availability for site visits across Canada and the USA, typically 1-2 times per quarter. Communication Skills: Excellent communication and interpersonal skills, with strong command of English, both written and verbal. Attention to Detail*: Highly organized, with strong p

About Altex Industries Inc. Altex Industries Inc. is a leading Canadian manufacturer specializing in the design, fabrication, and servicing of industrial air coolers, shell-and-tube heat exchangers, pressure vessels, and related heat transfer equipment for the Oil & Gas, Petrochemical, Power Generation, and Industrial sectors. With a strong reputation for quality, innovation, and customer service, we are committed to safety, continuous improvement, and strong collaboration across all departments. We are currently seeking experienced Mechanical Design Engineers to join our Engineering team in Edmonton, Alberta. Position Summary The Mechanical Design Engineer is responsible for the design, analysis, and execution of industrial air coolers, shell-and-tube heat exchangers, pressure vessels, and related heat transfer equipment. Working closely with customers, Project Management, Manufacturing, Quality Control, Supply Chain, and Field Services, this role supports projects from proposal and design through fabrication and delivery. The successful candidate will apply sound engineering principles to ensure equipment meets customer specifications, applicable codes and industry standards, and Altex quality requirements while supporting continuous improvement initiatives throughout the organization. Key Responsibilities Design industrial air coolers, finned tube bundles, shell-and-tube heat exchangers, pressure vessels, structural components, and related heat transfer equipment. Perform thermal and mechanical design calculations for air coolers, shell-and-tube heat exchangers, and related equipment. Perform or support mechanical design calculations for pressure-containing equipment in accordance with applicable ASME requirements. Prepare engineering calculations, fabrication drawings, bills of material, and supporting technical documentation. Review engineering calculations and drawings to ensure compliance with customer specifications, API 661, TEMA, ASME, other applicable codes and standards, and fabrication requirements. Support the development and improvement of air cooler, heat exchanger, and pressure equipment designs, manufacturing methods, and engineering standards. Manage assigned projects from design through fabrication and delivery. Work closely with Project Management, Manufacturing, Quality Control, Supply Chain, and Field Services to ensure successful project execution. Provide technical support to manufacturing operations and assist in resolving fabrication and design-related issues. Respond to customer inquiries and provide technical clarification throughout the project lifecycle. Conduct shop walk-downs to ensure design intent is maintained throughout fabrication. Assist in the preparation of change orders resulting from scope, schedule, or design changes. Participate in continuous improvement initiatives and engineering development projects. Perform other related duties as assigned. Qualifications ? Required Bachelor of Science in Mechanical Engineering. Professional Engineer (P.Eng.) designation and registration with APEGA. Minimum four (4) years of mechanical design experience in a manufacturing, fabrication, pressure equipment, or heat transfer equipment environment. Strong understanding of engineering principles, fabrication processes, and project execution. Experience preparing engineering calculations, drawings, and technical documentation. Excellent communication, organizational, and problem-solving skills. Ability to manage multiple projects and priorities in a fast-paced environment. Preferred Experience designing industrial air coolers and/or shell-and-tube heat exchangers, including thermal and mechanical design of heat transfer equipment. Knowledge and practical application of API 661 standards. Knowledge and practical application of TEMA standards for shell-and-tube heat exchangers. * Familiarity with ASME pressure equipment design and fabrication

Department: IT | Location: Can be based out of any US Location (Alachua, FL, Eden Prairie, MN, or West Lafayette, IN, or Remote) Base Salary: $95,000 - $110,000 Bonus Potential: $8,000 Applicants may be asked to complete a brief written exercise describing how they would investigate and respond to a cybersecurity incident in a regulated manufacturing environment. Why Join Evergen? Evergen is a global industry-leading contract development and manufacturing organization (CDMO) in regenerative medicine. As the only regenerative medicine company that offers a differentiated portfolio of allograft and xenograft biomaterials at scale, Evergen is headquartered in Alachua, FL, and has manufacturing facilities in West Lafayette, IN; Eden Prairie and Glencoe, MN; Neunkirchen, Germany; and Marton, New Zealand. We are proud to be Great Place to Work® Certified in 2026, reflecting our commitment to creating an exceptional employee experience and workplace culture. Help protect the technology, systems, and data that power life-changing medical device and regenerative medicine solutions. As a Cybersecurity Analyst, you'll play a critical role in safeguarding a highly regulated manufacturing environment while partnering with internal teams and a 24/7 Security Operations Center (SOC) to detect, respond to, and prevent cyber threats. This is a hands-on opportunity to make a direct impact, strengthen enterprise security, and help advance our cybersecurity maturity. Protect critical systems that support innovative regenerative medicine and medical device manufacturing. Work directly with cutting-edge cybersecurity technologies and a 24/7 SOC environment. Gain exposure to cloud security, incident response, threat detection, vulnerability management, and security governance. Influence enterprise-wide cybersecurity strategy and continuous improvement initiatives. Make a measurable impact in a mission-driven organization dedicated to improving patient outcomes. Key Responsibilities Serve as the primary on-site liaison for Evergen's 24/7 managed Security Operations Center (SOC), coordinating security activities and responding to escalated threats across the enterprise. Investigate and validate security alerts by gathering technical and business context, identifying potential impacts, and improving the quality and effectiveness of threat detection. Lead hands-on response efforts, including containment, remediation, and recovery activities such as endpoint isolation, account protection, and threat mitigation. Partner with SOC analysts to investigate incidents, perform root cause analysis, document findings, and continuously improve incident response playbooks and procedures. Collaborate with cybersecurity partners to enhance detection capabilities, tune security use cases, and identify opportunities to strengthen monitoring coverage. Support vulnerability management efforts by conducting security scans, assessing risk, prioritizing remediation activities, and tracking progress with technology owners. Participate in penetration testing, security assessments, and configuration reviews to strengthen defenses and reduce organizational risk. Help administer and optimize cybersecurity technologies, including endpoint protection, email security, logging, identity management, multifactor authentication, and privileged access controls. Support cybersecurity governance initiatives by helping implement security policies, regulatory requirements, and industry best practices. Gather evidence and support audits, customer assessments, risk reviews, and compliance activities within a regulated environment. Develop and report key cybersecurity metrics, including incident response performance, vulnerability remediation, and security program effectiveness. Automate routine security reporting, monitoring, and control validation activities to improve efficiency and scalability. Partner closely with the Cybersecurity Officer to execute strategic cybersecurity initiatives and provide security guidance to both technical and business teams. Promote a security-first culture by educating stakeholders and supporting continuous improvement across the organization. What You'll Bring Education Bachelor's degree in Cybersecurity, Information Technology, Computer Science, Engineering, or a related field; or an equivalent combination of education and experience. Experience 3+ years of cybersecurity or information security experience, including security operations, incident response, and collaboration with a managed SOC or MDR provider. Hands-on experience with threat monitoring, alert triage, vulnerability management, endpoint security, identity and access management, network security, and cloud security. Experience supporting audits, risk assessments, and compliance activities in regulated environments. Experience within medical device, healthcare, life sciences, manufacturing, or other highly regulated industries is preferred. Preferred Certifications CompTIA Security+, CySA+, GIAC GSEC, GIAC GCIH, or comparable cybersecurity certifications. Microsoft Security, cloud security, or other advanced cybersecurity certifications are a plus. Additional credentials in incident response, penetration testing, identity security, network security, cloud security, or risk management are highly valued. Technical & Professional Skills Strong understanding of cybersecurity principles, defense-in-depth strategies, and Zero Trust security frameworks. Experience analyzing security events, assessing risks, and implementing practical solutions. Proven incident investigation, troubleshooting, and root cause analysis skills. Working knowledge of cloud, network, endpoint, identity, and enterprise application security controls. Strong collaboration and relationship-building skills with both technical and non-technical stakeholders. Excellent written and verbal communication skills, including the ability to explain cybersecurity concepts to diverse audiences. Highly organized, detail-oriented, and driven by continuous improvement. Benefits Our comprehensive benefits package includes: Paid Time Off (PTO) 401(k) with company match Holiday pay Medical, dental, and vision insurance Short-term and long-term disability coverage Paid parental leave and much more! More About Evergen Evergen provides customers across a diverse set of market segments with leading-edge expertise, scale, and flexibility across end-to-end services including design, development, regulatory support, verification and validation, manufacturing, and supply chain management. Evergen is rooted in a steadfast commitment to quality, integrity, and patient safety with a focus on five key values: Accountable: We own our actions and decisions. Agile: We embrace change to stay ahead of the curve and evolve to drive innovation and growth. Growth Mindset: We embrace challenges as opportunities for continuous learning. Customer-Centric: We prioritize customers at every touch point. Inclusive: We thrive on the richness of our diversity and ensure every voice is heard, respected, and celebrated. At Evergen, we are committed to fostering an inclusive workplace where we embrace the richness of our diversity and ensure that every voice is heard, respected, and celebrated. We believe that by embracing diversity and promoting inclusivity, we not only uphold our values but also strengthen our position as the CDMO of Choice in regenerative medicine solutions. We recognize that cultivating a growth mindset is essential to our success, and we are dedicated to continuous learning and improvement in our diversity, equity, and inclusion efforts. Through accountability and action, we strive to create an environment where individuals can thrive, innovate, and contribute their unique perspectives to drive our collective success. Montagu Private Equity ("Montagu"), a leading European private equity firm, acquired RTI in 2020 and has supported the transformation of the company to its next level of potential.

As an MLOps Engineer on the Central Software (CSW) ML Platform team, you will play an active role in implementing the tools, infrastructure, and pipelines that unify how our product and research teams get stuff done. This is your chance to work closely with ML/RL engineers and researchers from across Boston Dynamics (BD), supporting advanced AI product and research activities at the forefront of robotics innovation. How You Will Make An Impact Transform proofs of concept into scalable solutions, helping product teams deliver new robot capabilities to customers Evolve and scale fielded solutions, enabling continuous model improvement and redeployment Work with stakeholders across BD to understand requirements, ensuring deployed solutions meet end-user needs Own end-to-end delivery of new capabilities, spanning implementation, testing, deployment, and operations Maintain our GPU clusters and develop automation to monitor and improve cluster health Use observability tools to monitor system health and root-cause problems across the platform Drive accuracy and efficiency by profiling and optimizing ML data, training, and evaluation pipelines. Work closely with other members of the ML Platform team to implement, deploy, and maintain ML infrastructure Be an active participant in our agile development process, coordinating work with others, calling out challenges, and regularly communicating progress Use your experience to mentor and upskill peers and other contributors across the organization You bring 5+ years of experience as a Senior Software Engineer or ML Engineer Proficiency in Python and related ML frameworks (PyTorch, TensorFlow, Pandas, NumPy) Experience with cloud platforms (e.g., GCP, AWS) and scalable ML deployment methods (Docker, Kubernetes, Ansible, Terraform) Experience with GPU cluster management and scheduling (e.g., Slurm, Kueue, or similar) Experience with CI/CD practices applied to ML pipelines Experience with experiment tracking and model/data versioning tools (e.g., MLflow, Weights & Biases, DVC) Experience building scalable data and ETL pipelines (e.g., Spark, Airflow) alongside data processing, augmentation, and cleaning techniques. Experience with Agile, Scrum, or other lean methodologies; ability to work collaboratively in cross-functional teams Bachelor's degree in Engineering, Computer Science, or a related technical field, or equivalent practical experience Nice to have Experience with networking fundamentals such as IAP, Tailscale, Shared VPC, NAT Familiarity with database optimization concepts such as indexing and connection pooling. Experience with TypeScript, Node, and related full-stack web technologies to build internal tooling, visualization dashboards, and web-based interfaces for MLOps platforms Experience with on-robot/edge deployment constraints (latency, compute limits, OTA model updates Experience with annotation tools such as SAM or Co-Tracker We are interested in all qualified candidates eligible to work in the United States. However, we are not able to sponsor visas for this position. The base pay range for this position is between $150,000 to $180,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and an annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.

Machine Learning Engineer III Primary Location : Cincinnati, OH V-Soft Consulting is currently hiring for a Machine Learning Engineer III for our premier client in Cincinnati, OH. Education and Experience: 5+ years of experience in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering. Demonstrated experience implementing end-to-end machine learning lifecycle management. Experience operating ML workloads in cloud environments (AWS, Azure, or GCP). Experience supporting both batch and real-time machine learning solutions. Experience working with large-scale structured and unstructured data. 3+ years of experience building and supporting production machine learning systems. Knowledge and Skills: ML Platform Engineering & Model Operations Design, develop, deploy, and manage production-grade machine learning solutions. Build scalable and reusable machine learning platforms that support model development, training, validation, deployment, and monitoring. MLOps Pipeline Development Design and maintain automated CI/CD/CT (Continuous Integration, Continuous Delivery, Continuous Training) pipelines for machine learning workflows. Automate model testing, validation, deployment, rollback, and retraining processes. Feature Store & Data Engineering Integration Design and support enterprise feature stores to improve feature reuse, consistency, and model governance. Collaborate with data engineering teams to integrate machine learning solutions with data warehouses, data lakes, and operational data sources. DevOps & Infrastructure Git/GitHub/GitLab Jenkins, GitHub Actions, Azure DevOps, or equivalent CI/CD tools Terraform or infrastructure-as-code frameworks Linux administration Shell scripting Production Monitoring & Reliability Implement model monitoring frameworks covering: Model performance Data quality Concept drift Feature drift System health and reliability Data drift Interested? Qualified candidates should send their resumes to lpanda@vsoftconsulting.com V-Soft Consulting Group is recognized among the top 100 fastest growing staffing companies in North America, V-Soft Consulting Group is headquartered in Louisville, KY with strategic locations in India, Canada and the U.S. V-Soft is known as an agile, innovative technology services company holding several awards and distinctions and has a wide variety of partnerships across diverse technology stacks. As a valued V-Soft Consultant, you're eligible for full benefits (Medical, Dental, Vision), a 401(k) plan, competitive compensation and more. V-Soft is partnered with numerous Fortune 500 companies, exceptionally positioned to advance your career growth. V-Soft Consulting provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. For more information or to view all our open jobs, please visit www.vsoftconsulting.com or call (844) 425-8425.

Job Posting End Date: November 01 Our Fortune 500 company is driving a digital transformation and looking for forward-thinking innovators to disrupt how our industry thinks about and uses technology. As one of the world's leading employee benefits providers, we help millions of people gain affordable access to benefits that help them protect their families, their finances and their futures. Are you an asker of questions, a solver of problems, and a challenger of the status quo? Our mission is to provide a differentiated customer experience and exceed the expectations people have of technology at any company — not just insurers. We are seeking individuals to join our team of talented IT professionals who share never-ending passion and an unwavering focus on our customer experience. Team members comfortable working in an agile, fast-paced, and delivery-focused environment thrive in our environment where we value an entrepreneurial spirit and those who challenge the status-quo. Unum is changing, and we're excited about what's next. Join us. General Summary We're looking for a Senior MLOps Engineer to help build, scale, and evolve the platforms that take machine learning models from experimentation to reliable production systems. This is primarily an MLOps role with exposure to GenAI and agentic AI. You'll work closely with data science and engineering teams to maintain and improve existing ML platforms, automate the model lifecycle, strengthen deployment and monitoring capabilities, and build new MLOps and AgentOps capabilities. You'll also help establish technical standards and mentor other engineers as the organization continues to mature its ML and AI engineering practices. Job Specifications Bachelor's degree in Computer Science, Information Technology, Information Systems, a related field, or equivalent relevant work experience. 5+ years of experience in software engineering, DevOps, ML engineering, MLOps, or a related discipline, with demonstrated experience supporting machine learning systems in production. Strong Python programming skills and software engineering fundamentals. Hands-on production MLOps experience across CI/CD, model deployment, model serving, and monitoring. Hands-on experience with AWS and cloud-based infrastructure. Strong experience with Docker and Kubernetes. Experience with Infrastructure as Code, such as Terraform. Hands-on experience contributing to at least one LLM or agentic AI project, such as a proof of concept, pilot, or production implementation. Relevant experience may include RAG, evaluation, versioning, monitoring, tracing, cost management, or guardrails. Experience with ML lifecycle and platform technologies. Databricks and MLflow are preferred, although comparable production MLOps tools and platforms will be considered. Experience building or maintaining CI/CD pipelines. Experience with GitHub Actions is preferred. Experience with observability and monitoring technologies. AWS CloudWatch and Databricks Lakehouse Monitoring experience is preferred. Strong communication and collaboration skills with the ability to work effectively across data science and engineering teams. Ability to mentor other engineers, influence technical direction, and help establish engineering standards without formal people-management responsibility. Preferred Qualifications Hands-on experience with Databricks, including capabilities such as Unity Catalog, Jobs/Workflows, Model Serving, and Lakehouse Monitoring. Experience with MLflow for ML lifecycle management. Experience supporting GenAI or agentic AI solutions beyond initial experimentation. Experience with AI/agent observability, evaluation, tracing, versioning, cost management, or guardrails. Background as a software/DevOps engineer who transitioned into MLOps, or an ML engineer with strong infrastructure engineering experience. Experience owning or improving an ML platform at scale. Principal Duties And Responsibilities Design, build, maintain, and scale production ML pipelines and platforms supporting model deployment, serving, monitoring, and lifecycle management. Build and improve CI/CD workflows for ML models, including automated testing, versioning, deployment, and release processes. Develop and operate scalable infrastructure supporting real-time and batch model inference. Implement monitoring and observability for ML systems, including model performance, system health, reliability, and operational issues. Help expand MLOps capabilities into GenAI and AgentOps, including areas such as evaluation, versioning, monitoring, tracing, cost management, and guardrails. Maintain and improve infrastructure using Infrastructure as Code, including Terraform or comparable technologies. Support ML lifecycle capabilities such as experiment tracking, model registries, model serving, and ML workflow orchestration. Partner with data scientists and engineers to improve the reliability, scalability, and maintainability of production ML solutions. Drive continuous improvements to deployment processes, monitoring, platform reliability, and developer experience. Establish and promote engineering standards around reproducibility, security, governance, and operational excellence. Mentor other engineers, contribute to technical design decisions, and help establish MLOps engineering standards across teams. ~IN1 Our company is built on helping individuals and families, and this starts with our employees. We want employees to maintain a positive balance, which is why we provide access to the benefits and resources they need to invest in themselves. From our onsite fitness facilities and generous paid time off to employee professional development programs, we are committed to helping employees live and work their best – both inside and outside the office. Unum is an equal opportunity employer, considering all qualified applicants and employees for hiring, placement, and advancement, without regard to a person's race, color, religion, national origin, age, genetic information, military status, gender, sexual orientation, gender identity or expression, disability, or protected veteran status. The base salary range for applicants for this position is listed below. Unless actual salary is indicated above in the job description, actual pay will be based on skill, geographical location and experience. $89,400.00-$183,500.00 Additionally, Unum offers a portfolio of benefits and rewards that are competitive and comprehensive including healthcare benefits (health, vision, dental), insurance benefits (short & long-term disability), performance-based incentive plans, paid time off, and a 401(k) retirement plan with an employer match up to 5% and an additional 4.5% contribution whether you contribute to the plan or not. All benefits are subject to the terms and conditions of individual Plans. Company Unum

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.

Job Description Why GMF Technology? Innovation isn't just a talking point at GM Financial, it's how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We're committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry. Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact. This position will be posted until filled. About The Role Apply AI/ML Engineering, Data Science, and Data Engineering practices to design, develop, test, launch, and maintain ML and LLM Operations capabilities. This position requires an understanding of the Data Science model development and Gen AI/LLM driven workflow lifecycle, MLFlow features, and the benefits of AI/ML product development and deployment. A general understanding of cloud architectures, software development principles CI/CD, deployment, APIs, microservices, Data and Dev ops, and Event-driven architectures is highly desirable. The ability to deliver solutions that are based on a business understanding is essential. Key responsibilities include enabling ML model and LLM-driven automation, and deployment to meet operational requirements like scalability, robustness, reusability, reproducibility, compliance, and responsible AI. This position requires expertise and passion for working in agile teams to plan effectively, collaborating with broader cross-functional teams, and successfully deliver mission-critical Data and AI projects. The Senior Machine Learning Operations Engineer is the subject matter expert in MLOps and LLMOps. They have good understanding of tools and technologies used to manage AI and ML Model Lifecycles. Provide technical support and coach junior ML Ops engineers. Responsibilities In this role you will: Develop enterprise-wide and scalable cloud-based MLOps, LLMOps capabilities that span the full life cycle of Machine Learning, Deep Learning and Generative AI models Develop reusable, secure, and robust AI and ML pipelines, monitor model performance, monitor data drift, utilize insights to train models, enable automatic audit trails, LLM traces creation for all artifacts, deploy across a wide range of business applications, and sustain a high level of automation across all AI/ML lifecycle activities. This includes developing code and making sure that AI/ML models are production ready Continuously improve the speed, quality, and efficiency of model/experiments development, production, and maintenance Collaborate with Model Management/Governance to develop and maintain enterprise-wide MLOps and LLMOps standards Collaborate with internal stakeholders and vendors in developing MLOps and LLMOps solutions that meet business requirements across a variety of areas including, but not limited to, Data Science, IT, Cybersecurity, Compliance, and Legal Maintain up to date knowledge about the latest advances in AI and ML Engineering, engage stakeholders, and champion proactive measures to sustain a cost effective, efficient, and innovative MLOps and LLMOps capabilities Develop and maintain a deep understanding of business requirements to ensure that MLOps and LLMOps solutions deliver practical and timely value Conduct AI and ML Engineering research and proof of concept projects to improve practice and develop business cases that support business needs Develop and apply algorithms that generate success metrics to improve the value of MLOps and LLMOps business function Presents findings and analysis for use in decision making and demonstrate bottom-line financial benefits (ROI) Collaborate with Business Teams, Data Architects, Data Engineers, Data Science and Cloud Solution Architects in developing solutions Prioritizes tasks and meets project deadlines in a fast-paced work environment Qualifications What makes you an ideal candidate? Proven experience in Azure ecosystem across the full AI/ML lifecycle with end-to-end automation (MLOps, LLMOPs), including ingestion and validation, dataset/version management, lineage and metadata tracking, feature engineering, experiment tracking, training, evaluation, pipeline-based validation gates, Responsible AI reviews, model registration, containerized deployment, event-driven monitoring, and integration like MLflow on Databricks or Azure Machine Learning Hands-on experience operationalizing GenAI solutions, including LLM application patterns such as Deep Research/RAG, prompt/version management, embedding workflows, model and prompt evaluation, safety/content filtering, human-in-the-loop review, and production monitoring (Tracing and Evaluations) for quality, latency, and cost Ability to understand and clearly articulate trade-offs of various approaches to solving AI and machine learning platforms e.g., Databricks vs. Azure ML pipelines, batch vs. streaming, AKS vs. Managed Serving endpoints, cost vs. performance, governance vs. speed Experience with event-driven architecture and streaming using Azure Event Hubs and Azure Function Apps Working knowledge in Azure DevOps or equivalent including GitHub Repos, Boards, CI/CD and other related functionality Experience delivering in agile environments (preferably SAFe) and partnering effectively with Data Science, Data Engineering, Application Engineering, Data Privacy and Security teams Strong software engineering fundamentals (testing, code quality, packaging, reusable modules, infrastructure-as-code mindset, observability, and secure-by-default design) Experience with large-scale data and lakehouse ecosystems, including Azure Databricks, Spark, and Delta-lake engines; Strong quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability, and statistics Ability to program in Python and SQL Experience with cloud deployment and runtime operations using Docker and Azure Kubernetes Service (AKS); familiarity with GitOps and environment promotion patterns is a plus Experience building/hosting ML and GenAI services using Azure App Services and/or AKS (APIs, asynchronous workers, scheduled jobs), with attention to reliability and production readiness Familiarity with the Azure AI ecosystem, including Azure AI Foundry, AI Services, Azure ML, and enterprise governance for model access, secrets, and data protection Strong applied ML understanding (e.g., regression, tree-based methods, neural networks, NLP) and the ability to translate business problems into measurable metrics and experiments Experience with BI/analytics tools (especially Power BI) and awareness of Data and Analytics platforms such as Azure Databricks Rapid prototyping and experimentation using low-code/no-code GenAI tools (e.g., Microsoft Copilot Studio) to quickly validate use cases, iterate on conversational flows, and transition successful prototypes into production-grade implementations Experience accelerating daily workflows with GenAI coding assistants (e.g., Databricks Genie, GitHub Copilot) while maintaining engineering rigor through code review, testing, security controls, and CI/CD Strong communication skills with the ability to explain complex concepts to senior stakeholders and connect technical delivery to measurable business and financial outcomes Proven ability to manage multiple workstreams in a time-sensitive environment and collaborate to solve problems creatively Experience/certification in Azure, Azure AI, ML, Databricks, or equivalent such as AWS and GCP, MLOps, Data architecture, container orchestration, streaming, H2O, Spark, and Linux Knowledge of Transactional, analytical databases and Data analysis techniques for structured, semi-structured, and unstructured data modeling and analysis (RDBMS, Columnar data-Parquet, JSON, etc.) Broad knowledge of networking concepts including TCP/IP, subnetting, routing, DHCP, and others is desirable Understanding of cybersecurity principles Work Experience & Education 4+ years as Data Scientist, Machine Learning Engineer, MLOps Engineer, AI Engineer or similar quantitative field required Azure Databricks experience preferred High School Diploma or equivalent required Master's Degree in the field of Computer Science/Engineering, Analytics, Mathematics, or related discipline required PhD preferred What We Offer : Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays. Our Culture : Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive. Compensation : Competitive pay and bonus eligibility. Work Life Balance : Flexible hybrid work environment, 2-days a week in office. NOTE: We are unable to consider candidates who require visa sponsorship for this position This position is not open to agency submissions #GMFJobs

Who We Are: At OPENLANE we make wholesale easy so our customers can be more successful. We're a technology company building the world's most advanced—and uncomplicated—digital marketplace for used vehicles. We're a data company helping customers buy and sell smarter with clear, actionable insights they can understand and use. And we're an innovation company accelerating the future of wholesale remarketing through curiosity, collaboration, and an entrepreneurial spirit. Our Values: Driven Waybuilders. We pursue challenges that inspire us to build, create, and innovate. Relentless Curiosity. We seek to understand and improve our customers' experience. Smart Risk-Taking. We transform risk into progress through data, experience, and intuition. Fearless Ownership. We deliver what we promise and learn along the way. We're Looking For An Machine Learning Operations (MLOps) Engineer who builds and operates the pipelines, platforms, and observability that carry machine learning models from experimentation into reliable, cost-efficient production. You will join a new MLOps team within Site Reliability Engineering and help define how OPENLANE trains, ships, monitors, and safely updates models at scale. You will independently design automated ML delivery workflows, reduce operational toil, and ensure models are reproducible, monitored, and serving predictions safely in production. You Are Analytical, pragmatic, proactive, collaborative, quality-focused, and AI-forward. You treat AI as a first-class engineering tool, critically evaluate its output, and apply strong engineering judgment to systems that must stay healthy long after the first deployment. You Bring Core knowledge of system architecture, distributed systems, cloud-native design, networking, and agile development methodologies (Scrum, Kanban). Functional expertise in designing end-to-end ML pipelines (data ingestion, training, validation, deployment), including requirements for latency, redundancy, scalability, and error handling. Technical expertise in CI/CD for ML, infrastructure-as-code, containerization and orchestration, and metrics, monitoring, and alerting toolsets. Working understanding of the model lifecycle: experiment tracking and lineage, model registries, model drift, data quality, and retraining triggers, with enough ML fluency to diagnose model issues alongside data scientists. Strong Python skills and the ability to write clean, well-tested, production-ready code. You Own Design, build, and operation of automated ML pipelines covering data ingestion, training, validation, deployment, and rollback. Model CI/CD, including automated testing and canary and rollback strategies for safe releases. Monitoring and observability for model performance, data drift, inference latency, and availability, with actionable alerting and incident response. Reproducibility of model workloads through versioned code, data, features, and environments. Identification and reduction of operational toil through automation, standardization, and reusable ML platform components. Documentation, testing, and debugging of pipelines and serving infrastructure, maintaining high code and design standards. You Drive Execution: Translate data science and product needs into scalable, automated ML delivery designs, and implement technical roadmap projects for the MLOps platform. Results: Shorten time-to-production for models while improving reliability, minimizing failure risk, and optimizing the cost, scaling, and utilization of training and inference workloads in partnership with Infrastructure teams. Team: Support hiring, knowledge sharing, and mentorship as the MLOps practice grows. How You'll Use AI in This Role AI-assisted coding, refactoring, and test generation for pipelines and platform tooling. AI-supported debugging and root-cause analysis of pipeline failures and model degradation. AI-assisted documentation and runbooks to reduce repetitive work and increase engineering leverage. Who You Will Work With Reporting to the Director, Site Reliability Engineering, this role collaborates daily with Data Scientists, Data Engineers, Software Engineers, Infrastructure, Security, Product Owners, and SRE teams across the organization. Where You Work Your work is performed as a Remote employee, with occasional team alignment meetings as needed. Must Have's 3+ years of experience in MLOps, ML engineering, Site Reliability Engineering, DevOps, or Software Engineering, including experience building or operating ML pipelines in production. Bachelor's degree preferred or equivalent practical experience. Strong Python skills and hands-on experience with a major cloud platform (AWS preferred). Experience with workflow orchestration (e.g., Airflow, Kubeflow, Step Functions), infrastructure-as-code (e.g., Terraform), and CI/CD systems. Experience with containers and Kubernetes (Docker, EKS preferred). Familiarity with model serving frameworks (e.g., TorchServe, TF Serving, Triton, BentoML, SageMaker endpoints) and monitoring tools (e.g., Prometheus, Grafana, Evidently AI). Hands-on experience with system debugging, observability, and incident response in production environments. Actively uses AI development tools and can critically evaluate AI outputs. Nice to Have's Experience with ML platforms and tooling such as SageMaker, MLflow, Databricks, or Vertex AI (GCP). Experience with feature stores, model registries, or LLM/GenAI deployment and evaluation (LLMOps). Experience with GPU workload scheduling and inference cost optimization. Experience interviewing candidates, conducting technical debriefs, and mentoring junior engineers or interns. Proven ability to acquire deep domain and architectural knowledge within 6 months of joining a team. What We Offer: Competitive pay Medical, dental, and vision benefits with employer HSA contributions (US) and FSA options (US) Immediately vested 401K (US) or RRSP (Canada) with company match Paid Vacation, Personal, and Sick Time Paid maternity and paternity leave (US) Employer-paid short-term disability, long-term disability, life insurance, and AD&D (US) Robust Employee Assistance Program Employer paid Leap into Service Day to volunteer Tuition Reimbursement for eligible programs Opportunities to expand your skill set and share your knowledge across a publicly traded, global organization Company culture of internal promotions, diverse career paths, and meaningful advancement Sound like a match? Apply Now - We can't wait to hear from you!

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.

Job Title: AI Prompt Engineer Job Category: Information Technology Time Type: Full time Minimum Clearance Required to Start: None Employee Type: Regular Percentage of Travel Required: Up to 10% Type of Travel: Local The Opportunity CACI is seeking a forward-thinking AI Prompt Engineer to join a team delivering innovative AI solutions in support of U.S. Customs and Border Protection (CBP). This is a unique opportunity to apply cutting-edge generative AI technologies to one of the nation's most critical missions. In this role, you will help modernize how frontline personnel access information, make decisions, and execute their work. By leveraging AI-powered tools and large language models, you will develop solutions that improve efficiency, enhance situational awareness, and accelerate access to mission-critical information. Your work will directly support the men and women responsible for protecting our nation's borders, facilitating lawful trade and travel, and safeguarding our nation. You will be part of CACI's Agile Solution Factory, a collaborative environment focused on rapid innovation, experimentation, and continuous learning. We are seeking individuals who combine creativity, technical curiosity, and a passion for exploring the evolving capabilities of AI. The ideal candidate can translate complex operational challenges into practical, high-impact AI solutions that deliver measurable value to mission users. Candidates will participate in a structured AI Prompt Engineering training program prior to transitioning to a client facing assignment. Responsibilities Prompt Design & Optimization: Develop, refine, and iterate on prompts for various generative AI models (LLMs) to elicit desired behaviors, responses, and creative outputs. Iterative Testing & Analysis: Conduct testing to compare prompt variations, analyze results drive continuous improvement. Collaboration: Work closely with multiple groups to integrate prompts to streamline manual processes. Research & Development: Stay abreast of the latest advancements in LLMs, generative AI, and prompt engineering techniques. Fine-tuning & RAG Support: Provide input and collaborate on strategies for model fine-tuning and Retrieval Augmented Generation (RAG) to further improve accuracy. Problem Solving: Debug unexpected model behaviors, identifying root causes within prompt structure, model limitations, or data context. Qualifications Required: Must be a U.S. Citizen with the ability to pass CBP background investigation, criteria include, but not limited to: 3-year check for felony convictions 1 year check for illegal drug use 1 year check for misconduct such as theft or fraud High School diploma or equivalent completed prior to start Must be available to work onsite in Ashburn, VA and/or Washington, D.C. Problem-solving skills, with a data-driven approach to experimentation and optimization. Written and verbal communication skills, with an ability to articulate complex technical concepts clearly. Ability to work independently and collaboratively in a fast-paced, evolving environment. Desired Software development experience, internships, or relevant academic project work. Hands-on experience working with Large Language Models (e.g., OpenAI GPT series, Llama, Gemini) or other generative AI models. Experience with any programming language (Python, JavaScript/TypeScript, etc.) Familiarity with prompt engineering techniques (few-shot, chain-of-thought, structured outputs, function calling) Exposure to RAG concepts, including embeddings and vector databases Understanding of AI safety considerations (e.g., prompt injection, bias, data privacy) Exposure to Agile/Scrum development environments This position is contingent on funding and may not be filled immediately. However, this position is representative of positions within CACI that are consistently available. Individuals who apply may also be considered for other positions at CACI. What You Can Expect A culture of integrity. At CACI, we place character and innovation at the center of everything we do. As a valued team member, you'll be part of a high-performing group dedicated to our customer's missions and driven by a higher purpose – to ensure the safety of our nation. An environment of trust. CACI values the unique contributions that every employee brings to our company and our customers - every day. You'll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality. A focus on continuous growth. Together, we will advance our nation's most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy. Pay Range There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits. Since this position can be worked in more than one location, the range shown is the national average for the position. The Proposed Salary Range For This Position Is $39,400-$72,600 CACI is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any other protected characteristic.