Health AI Systems Architect

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.

• 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 כמו consider 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 trade‑off 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.

• 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.

• 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.
• Direitos 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.

• 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.קומען
• 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:

Remote.

Travel:
Periodic travel may be required.

Clearance:
Ability to obtain HHS Public Trust.

Equal employment opportunity, including veterans and individuals with disabilities.

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