AI​/ML Architect

Job Summary

We are seeking an experienced AI/ML Architect to support the Department of Veterans Affairs (VA) in shaping the strategy, governance, and operational frameworks that guide enterprise-wide artificial intelligence and machine learning initiatives. In this role, you will design and maintain robust AI product management pipelines that enable the VA to responsibly deploy and scale AI/ML solutions across its healthcare and benefits delivery mission.

Your work will directly impact the quality of care and services delivered to millions of U.S. Veterans by ensuring AI systems are developed, monitored, and governed in alignment with federal policy and VA standards. The ideal candidate is a technically fluent, strategically minded professional who thrives at the intersection of cutting-edge ML engineering and enterprise-scale governance, bringing both hands‑on MLOps expertise and the organizational savvy to influence policy and stakeholder decision‑making in a complex federal environment.

Design, establish, and maintain enterprise-level AI/ML product management pipelines that support the full model lifecycle — from data ingestion and experimentation through deployment, monitoring, and decommissioning — aligned with VA governance standards. Develop and document AI/ML architecture blueprints, reference architectures, and technical standards that guide development teams across VA programs and ensure consistency, scalability, and compliance with federal AI policy (including OMB AI guidance and VA Directive 6500 series).

Partner with VA AI governance bodies, program offices, and contracting leadership to assess AI product readiness, identify pipeline gaps, and recommend MLOps tooling, platforms, and process improvements that accelerate responsible AI adoption. Define and implement model risk management practices, including bias detection, model drift monitoring, explainability frameworks, and audit‑trail requirements, ensuring deployed AI/ML systems meet VA and federal responsible AI standards.

Collaborate with data engineers, data scientists, software engineers, and product managers to translate business requirements into scalable ML system designs, and provide technical oversight during iterative development and CI/CD pipeline integration. Prepare and present technical briefings, white papers, and strategic roadmaps for senior VA leadership and stakeholders, communicating complex AI/ML architecture concepts and governance recommendations in clear, mission‑aligned terms.

5+ years of hands‑on experience in AI/ML architecture, data science engineering, or a closely related technical discipline, with demonstrated experience establishing or maintaining enterprise‑level AI/ML product management pipelines. No minimum education requirement specified; equivalent combination of technical training, professional certifications, and direct experience in AI/ML systems architecture will be fully considered. Prior experience supporting federal agency clients or large‑scale regulated‑industry environments (e.g., healthcare, finance, defense) where AI governance, data privacy, and compliance requirements shape ML system design.

Ability to obtain and maintain a VA Position of Public Trust (suitability clearance) as required for access to VA systems and sensitive Veterans' data; active clearance or prior VA/federal suitability a plus. Must be legally authorized to work in the United States without current or future sponsorship; U.S. citizenship may be required to satisfy VA network access and background investigation requirements.

Deep familiarity with MLOps frameworks, platforms, and tools (e.g., MLflow, Kubeflow, Sage Maker, Azure ML, Data Robot) and modern CI/CD practices for ML systems, including model versioning, pipeline orchestration, and automated testing.

1. Experience working directly within or in support of VA, HHS, DoD, or another federal health agency AI/data program, with working knowledge of VA‑specific data environments (e.g., CDW, VINCI, VistA). 2. Familiarity with federal AI governance frameworks, including the NIST AI Risk…