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Senior AI Engineer
Skills
BiotechnologyData WarehousingDecision SupportDriftHealth InformaticsHealthcareProduction Deployment
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 4+ years building and operating LLM powered or production ML systems
- Strong Python skills
- Deep familiarity with at least one production backend framework such as FastAPI or Flask
- Hands on experience with LLM orchestration function calling and retrieval system design
- Working knowledge of a cloud data warehouse such as Snowflake
- Modern data tooling experience such as dbt Dagster or Airflow
- Track record of designing evaluation systems for LLM applications
- Familiarity with safety considerations for LLM applications
- Practical understanding of HIPAA BAAs and PHI handling
- Strong written communication for design docs and technical RFCs
Nice to have
- Bias to ship
- Scrappy
- Fast learner
- Strong ownership
- Mentorship
Day to day
- Own the design development and production deployment of LLM powered systems for clinicians and members
- Build agentic medical companions clinical decision support tools and document understanding pipelines that convert unstructured clinical data into usable signal
- Develop end to end AI systems across orchestration retrieval evaluation and deployment with strong emphasis on reliability safety observability and real world adoption
- Partner with clinicians data engineers and research collaborators to translate clinical requirements into robust AI products and mentor peers on applied AI best practices