Teams at Midi Health

Design, build, and own end-to-end unit-economics frameworks linking acquisition, multi-product lifecycles, reimbursement, and costs. Develop LTV/reimbursement models, attribution and pricing experiments, causal uplift models for churn interventions, and Monte Carlo simulations to stress-test business scenarios. Partner with finance, marketing, and operations and deploy production-grade models influencing strategic decisions.

Build and deploy LLM-powered features for clinical, patient, and operational workflows. Responsibilities include prompt design, retrieval, tool use, agent orchestration, evaluation harnesses, feedback loops, production operations, and AI engineering tooling. Partner with clinical, product, and safety stakeholders to ensure responsible healthcare-grade AI. Mentor teammates, communicate model behavior clearly, and stay current with emerging AI research and development practices.

Leads AI engineering strategy across clinical, patient, and operational products. Designs and operates production retrieval, orchestration, agentic, and evaluation systems, establishing standards for AI safety, observability, responsible deployment, and reliability. Partners with clinical, product, and executive leaders on the AI roadmap, mentors engineers, evaluates emerging models and tools, and codes regularly in Python.