Manager of Applied AI Products
RemoteUnited States
Job Summary
Design and ship AI features for MedicatOne, personally writing production code for LLM integrations, RAG pipelines, and vector search while owning architecture from data ingestion to deployment. Partner with the Product Manager and CTPO to shape the AI roadmap, translating provider pain points into scoped proposals and establishing evaluation frameworks for clinical utility. Serve as a senior point of contact for strategic client conversations, leading discovery sessions with health center directors to validate product direction and inform RFP responses. Act as the final technical reviewer for employee-created AI tools, ensuring reliability, security, and HIPAA compliance before production use. Guide non-engineering teams on responsible AI adoption through code reviews, pairing, and direct feedback to raise the technical bar across the organization. This player/coach role requires genuine fluency in clinical workflows and healthcare data standards to deliver AI capabilities that meaningfully improve operational systems for college health and counseling clinics.
Required Qualifications
- Must currently reside in the United States
- Must be authorized to work in the US without visa sponsorship
- Candidates without a substantive healthcare IT background will not be considered
- Meaningful experience in healthcare SaaS, health systems, or digital health
- Experience working with or inside an EHR environment
- Working knowledge of healthcare data standards: HL7 v2, FHIR (R4 preferred), CCD/CCDA, and common interoperability patterns
- Familiarity with clinical workflow design
- Direct experience navigating HIPAA compliance, PHI handling, de-identification, and the privacy constraints that shape system design in regulated healthcare environments
- 6+ years in product engineering, technical product management, or a hands-on hybrid role in B2B SaaS
- At least 3 years personally building AI or ML-powered features in production
- A portfolio of AI work you built yourself
- Hands-on experience with LLM API integration (OpenAI, Anthropic, or similar) in production healthcare or enterprise environments
- Working knowledge of RAG architectures: retrieval pipeline design, chunking strategies, grounding, and evaluation
- Familiarity with vector databases, embedding models, and unstructured data indexing
- Comfortable with data modeling, SQL, and analytics workflows over large structured healthcare datasets
- API design and backend services experience sufficient to review and guide engineering decisions
- Strong written and verbal communication
- Able to operate across the strategic and tactical
Desired Qualifications
- Exposure to college health, student health, or behavioral health contexts
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