A well-funded startup building intelligent systems for pharmaceutical research and clinical operations.
AI Engineer
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You'll spend mornings refining retrieval pipelines that help research teams surface relevant protocols from messy document collections. Afternoons often go to prompt engineering—coaxing better structured outputs from LLMs so downstream analytics become more reliable. Sometimes you'll prototype a tool that predicts trial bottlenecks; other times you'll untangle why a chain's context window is swallowing the wrong chunks. The work sits at the intersection of messy real-world healthcare data and models that still hallucinate, which means your judgment matters as much as your technical chops.
What they're looking for
- 2–7 years shipping Python in production, with substantial exposure to LLM frameworks like LangChain or equivalent orchestration layers
- Demonstrated ability to design retrieval-augmented generation systems and evaluate them beyond naive accuracy metrics
- Comfort operating where regulatory constraints and technical ambition collide—healthcare or adjacent regulated industries preferred
- Strong written communication; you can explain a failing embedding strategy to a biostatistician without jargon
- Based in San Francisco or New York metro, willing to collaborate in person several days weekly