Strategic Analysis, Inc. (SA) Is actively seeking a Health AI Systems Architect to provide technical and architectural oversight for complex, multi-stakeholder programs advancing AI-enabled systems in healthcare. This is a Science and Engineering and Technical Advisor (SETA) role focused on ensuring that program-wide technical architecture—spanning data, infrastructure, governance, and security—supports rigorous AI development, evaluation, and long-term impact.

The Health AI Systems Architect will operate at the system-of-systems level, advising program leadership and external performers on how diverse technical components fit together across the full lifecycle of the program. These components include aggregation of existing healthcare data, collection of new data, and development of shared data infrastructure to support AI development, benchmarking, and downstream research use.
This role is ideal for someone who combines deep technical understanding of health data and AI systems with strong architectural judgment, and who can translate complex technical tradeoffs into clear, actionable guidance for program leadership and partners.

Roles and Responsibilities:
-Provide program-level architectural guidance across multiple technical components, including data aggregation, new data generation, and shared data infrastructure.
-Advise on end-to-end data flows, from source systems through curation, access, evaluation, and downstream reuse.
-Review and assess technical architectures and system designs proposed by external teams for feasibility, scalability, security, and alignment with program objectives.
-Provide guidance on data governance, privacy, and security models, including access control, auditing, and compliance considerations.
-Advise on dataset construction, documentation, versioning, and lifecycle management to support reproducibility and reuse.
-Provide technical input on synthetic data strategies, including appropriate use cases, limitations, and validation considerations in healthcare contexts.
-Assess infrastructure and compute considerations, including scalability, interoperability, and cost tradeoffs.
-Identify system-level risks (e.g., fragmentation, misaligned interfaces, governance gaps) and recommend mitigation strategies.
-Serve as a technical liaison between infrastructure teams, data contributors, AI developers, clinical SMEs, and program leadership.
-Support program leadership with technical assessments, architectural recommendations, and tradeoff analyses.
-Contribute to technical documentation, architecture briefs, and presentations for internal and external stakeholders.
-Help ensure that technical decisions support long-term sustainability, interoperability, and real-world clinical relevance.

This role is suited to candidates who:
-Operate with a high degree of ownership and accountability.
-Think in end-to-end systems rather than isolated components.
-Are comfortable making and defending architectural tradeoffs under uncertainty.
-Exhibit initiative and independence, and perform effectively in ambiguous, fast-moving environments.
-Maintain exceptional rigor and precision, with high standards for technical quality.
-Communicate complex technical concepts clearly and professionally to diverse audiences.
-Bring a mission-driven mindset, motivated by advancing AI systems with real clinical and patient impact.

Minimum Qualifications:
-Advanced degree (Master’s or PhD) in Computer Science, Biomedical Informatics, Systems Engineering, Data Science, or a related field.
-7+ years of experience designing, evaluating, or overseeing complex data-intensive systems, preferably in healthcare or life sciences.
-Deep familiarity with healthcare data types (e.g., EHR, imaging, genomic, multimodal) and their architectural implications.
-Strong understanding of data governance, privacy, and security principles relevant to health data.
-Experience designing or evaluating data platforms, data commons, or shared research infrastructure.
-Ability to reason about infrastructure, compute, storage, access control, and scalability trade-offs at a system level.
-Demonstrated ability to review and critique technical architectures and system designs proposed by external teams.
-Strong written and verbal communication skills, with experience producing high-quality technical documentation and presentations.

Preferred Qualifications:
-Familiarity with synthetic data generation and validation in healthcare or biomedical contexts.
-Prior experience in technical advisory, evaluation, or SETA-style roles.
-Experience working across multi-institution or multi-performer programs.
-Familiarity with health data interoperability standards and their application in large-scale data systems.
-Experience working in early-stage, fast-paced, startup environments.

Education: Master's degree (PhD preferred) in Biomedical Informatics, Data Science, Biostatistics, or a related field.

Location: Position is remote.

Travel: Periodic travel may be required

Clearance: Ability to obtain HHS Public Trust.