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Salary: USD 210,000 - 250,000 / annual
Midi Health is the largest virtual care clinic for women navigating perimenopause, menopause, and hormonal transitions. The company combines expert clinicians, evidence-based protocols, and modern technology to deliver historically underserved care.
You will set the direction for how Midi builds with AI across clinical workflows, patient experience, and operational intelligence. You'll own the architecture of AI systems, evaluation practices that keep them safe, and standards that let every engineer ship AI features confidently. This role defines what AI engineering looks like in a modern healthcare company.
Key responsibilities:
- Lead technical strategy for AI/LLM systems across Midi's product surfaces
- Architect retrieval, orchestration, agentic, and evaluation systems that run reliably in production
- Set standards for AI safety, evaluation, observability, and responsible rollout in healthcare context
- Partner with clinical, product, and executive leadership to shape the AI roadmap
- Mentor senior and mid-level engineers into strong AI engineers; raise AI literacy across the organization
- Evaluate new models, techniques, and tools; bring the right ones into the team
The company operates hybrid by design: two days per week in-office (Tuesday/Thursday) in Palo Alto or San Francisco. Culture emphasizes AI-native engineering (fluency with Claude Code, Cursor, Copilot), low-ego collaboration, and outcome-oriented execution.
Requirements:
- 10+ years of software engineering experience with deep recent time leading production AI/LLM systems
- Seasoned hands-on coder; writes production Python regularly
- Seasoned system designer for AI systems at scale (retrieval, agents, evaluation, latency, cost)
- Authority in AI engineering: teams and leaders defer to your judgment, defended rigorously
- Leader at the AI frontier: set how the team uses AI tooling and builds AI products
- Seasoned mentor with track record growing engineers into strong AI builders
- Strong communicator with product, clinical, and executive stakeholders; thoughtful about risk and safety tradeoffs
- Low-ego, curious, humble
Nice to have:
- Healthcare, clinical NLP, or regulated AI deployment experience
- Track record shipping agentic or large-scale RAG systems in production
