AI Engineer (Clinical AI Data + Retrieval) — San Francisco (On-site) | $170–250k + equity

I’m working with a well-funded SF healthcare startup building a consumer primary care product that combines patient records + AI + real clinicians to deliver fast, explainable, citation-backed medical answers.

They’re hiring an AI Engineer to own the data + retrieval foundation behind the clinical AI. This is not prompt tinkering - it’s systems work: pipelines, traceability, correctness, observability, and performance.

What you’ll do

Build/improve a clinical knowledge base where citations resolve to original sources
Improve retrieval quality (RAG / grounding / vector search) with strong data lineage
Rebuild data ingestion + integrity to eliminate stale data & support corrections
Implement observability for background jobs (tracing, failure analysis, auditing)
Design data portability + deletion workflows with privacy built-in

Must-haves

Strong Python + SQL
Production Postgres (JSONB; vector is a plus)
Proven refactors / migrations / simplifying messy data systems
Comfort owning problems end-to-end (schema → service → prod debugging)
Good judgment around correctness and tradeoffs

Nice-to-haves

RAG pipelines, vector search, eval frameworks
FastAPI / SQLAlchemy / DuckDB / Temporal / ClickHouse / Valkey
Langfuse/Sentry-style observability + Docker/ECS deployments
Experience with regulated or sensitive data (bonus, not required)

Package

$170k–$250k + equity (level depends on ownership/scope)
On-site in San Francisco (non-negotiable)

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