AI/ML Architect

Aptive•Remote,

4d•Remote

About The Position

Aptive Resources is seeking an AI/ML Architect to collaborate with program and project leaders in defining and creating architectural depictions and documents, and to design and discuss system strategies for platform, applications, and networks. This role will shape how AI systems are built, deployed, monitored, and retired across the VHA enterprise. The architect will draft reference architectures and MLOps standards for innovators and central teams, and provide hands-on technical consultation to early-stage AI products from VHA facilities. This is a full-time, remote, contingent hire position.

Requirements

5 years minimum of software or systems architecture experience.
Able to work with program and project leaders to define and create the architectural depictions and documents, ensuring logical flow, and address all issues.
Experience with a variety of software programs and languages and some experience in programming.
Able to design and discuss system strategies for platform, applications, and networks.
Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
Must be able to obtain and maintain a favorably adjudicated Tier 1 / National Agency Check with Written Inquiries (NACI) background investigation in accordance with VA Handbook 0710.
Must complete VA Privacy and Information Security Awareness and Rules of Behavior training (TMS #10176) prior to system access and annually thereafter.
Must be authorized to work in the United States.
All work must be performed within a jurisdiction subject to the law of the United States or its territories.

Nice To Haves

Ten or more years of architecture experience, including five or more establishing or maintaining enterprise-level AI/ML product pipelines.
MS preferred.
Cloud architect certification (Microsoft Azure, AWS, or Google Cloud) preferred.
Experience with a variety of software programs and languages, with hands-on programming ability retained.
Hands-on MLOps depth: model registry, CI/CD pipelines for models, automated retraining, monitoring and drift detection, feature stores, and model cards.
Experience with VA Arches or a comparable accredited federal AI and analytics platform.
Working knowledge of healthcare data standards and sources such as FHIR, HL7, OMOP, and EHR or clinical data warehouse environments.
Cloud architecture experience in Microsoft Azure, AWS, or Google Cloud.
Experience conducting technical due diligence on vendor AI products and writing the findings up for a non-technical decision maker.
Familiarity with FedRAMP and Authority to Operate processes in a federal environment.
Agile and SAFe delivery experience.
Ability to write reference architecture and standards documentation that engineers outside your team can actually follow.
Ability to get up to speed quickly on complex issues; desire to work in a fast-paced, rapidly evolving environment.
Capable self-starter with a drive to get all types of work done and high attention to detail.
Outstanding written and verbal communications skills.
Knowledge of military and Veteran populations.

Responsibilities

Work with program and project leaders to define and create architectural depictions and documents for AI systems developed and deployed across the VHA enterprise, ensuring logical flow and resolving open technical issues.
Draft reference architectures and recommend MLOps standards for VHA adoption, and design and discuss system strategies for platform, applications, and networks.
Author the technical content of AI entrepreneur and adopter playbooks covering both internal development and vendor evaluation pathways.
Provide technical consultation to early-stage AI products across five field pilot partnerships, from concept through deployment readiness.
Recommend AI product lifecycle standards (model registry, CI/CD for models, automated retraining, monitoring and drift detection, and model documentation).
Develop the AI catalog redesign plan in collaboration with VA IT teams to improve the current AI use case inventory platform.
Evaluate third-party and vendor AI solutions against VHA technical, security, and interoperability requirements.
Translate VA security and authorization requirements into architecture decisions that field teams can execute (VA Handbook 6500, VA Handbook 6517, Assessment and Authorization and ATO processes, FedRAMP).
Contribute technical depth to AI risk management playbooks and oversight assessment guides, particularly on model validation and post-deployment monitoring.
Support the AI center of excellence operational playbook with the technical infrastructure and tooling model.