AI/ML Architect

Aptive; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

Aptive seeks an experienced AI/ML Architect to support the Department of Veterans Affairs in shaping strategy, governance, and operational frameworks for enterprise-wide AI/ML initiatives. You will design and maintain robust AI product management pipelines enabling responsible deployment and scaling across VA healthcare and benefits missions.

The role requires hands-on MLOps expertise, architecture design, and the ability to influence policy and stakeholder decisions in a federal environment.

Qualifications

• 5+ years in AI/ML architecture or related technical discipline.
• Experience building enterprise-level AI/ML product management pipelines.
• Ability to obtain VA Position of Public Trust clearance; U.S. citizenship may be required.

Responsibilities

• Design and maintain enterprise-level AI/ML product management pipelines across the full model lifecycle.
• Develop AI architecture blueprints, reference architectures, and technical standards for VA programs.
• Collaborate with data engineers, data scientists, software engineers, and PMs to translate requirements into scalable ML designs.
• Prepare technical briefings and roadmaps for senior VA leadership.

Skills

AI/ML architecture

Data science engineering

MLOps

CI/CD for ML

Govt experience

Tools

MLflow

Kubeflow

SageMaker

Azure ML

DataRobot

Job description

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.

Primary Responsibilities

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.

Minimum Qualifications

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, SageMaker, Azure ML, DataRobot) and modern CI/CD practices for ML systems, including model versioning, pipeline orchestration, and automated testing.

Desired Qualifications

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 Management Framework (AI RMF 1.0), Executive Order 13960/14110 on Trustworthy AI, and OMB Memoranda on AI in government. 3. Experience designing AI/ML systems that handle Protected Health Information (PHI) and Personally Identifiable Information (PII) in compliance with HIPAA, the Privacy Act, and FedRAMP security requirements. 4. Demonstrated ability to build or mature an AI Center of Excellence (CoE), AI governance board, or model registry function within a large enterprise or government program. 5. Proficiency in cloud‑native ML architectures on AWS GovCloud, Microsoft Azure Government, or Google Cloud's government offerings, including experience with ATO (Authority to Operate) processes for AI‑enabled systems.

About Aptive

About Aptive. Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human‑centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.

EEO Statement

Aptive is an equal opportunity employer. We consider all qualified applicants for employment without regard to race, color, national origin, religion, creed, sex, sexual orientation, gender identity, marital status, parental status, veteran status, age, disability, or any other protected class. Veterans, members of the Reserve and National Guard, and transitioning active‑duty service members are highly encouraged to apply. About Aptive: Aptive partners with federal agencies to achieve their missions through improved performance, streamlined operations and enhanced service delivery. Based in Alexandria, Virginia, we support more than a dozen agencies including Veterans Affairs, Transportation, Defense, Homeland Security and the National Science Foundation. We specialize in applying technology, creativity and human‑centered services to optimize mission delivery and improve experiences for millions of people who count on government services every day. Founded: 2012. Employees: 300+ nationwide.