Member of Technical Staff - Forward Deployed AI Engineer, Health

Overview At Microsoft AI, our Health team is on a mission to help millions of people better understand and proactively manage their health and wellbeing. We are responsible for ensuring that Microsoft AI's models, products, and services are useful, trusted, and safe across diverse health journeys. Microsoft AI and Mayo Clinic have announced a strategic collaboration to develop and deploy a frontier AI model designed specifically for healthcare. The collaboration combines Mayo Clinic's clinical expertise, de-identified clinical health data, longitudinal insights, and trusted environment with Microsoft's advanced AI, cloud, engineering, and superintelligence capabilities. The model will initially be deployed within Mayo Clinic, where it can be tested, refined, and improved through real-world use. We are looking for a Forward Deployed AI Engineer to join the Microsoft AI Health team and play a leading technical role in this collaboration. This is a very senior, deeply hands-on individual-contributor position at the intersection of Applied AI, platform engineering, data engineering, and forward-deployed delivery. You will act as a technical lead for the engineering work between Microsoft AI and Mayo Clinic. You will embed closely with teams across both organizations, understand a complex environment of clinical data platforms and legacy systems, and identify the shortest path fr [... source excerpt omitted ...] learning unfamiliar systems quickly, building trust across a large stakeholder network, and finding pragmatic ways through technical, organizational, and operational constraints. You will not stop at recommendations or prototypes: you will build alongside partner teams and remain accountable through integration, deployment, validation, and adoption. The goal is both to deliver the Mayo Clinic collaboration and to strengthen the platform beneath it. You will turn partner-specific learning into reusable infrastructure, data capabilities, integration patterns, and paved paths that can support the frontier healthcare model and future health AI products. Responsibilities Serve as [... source excerpt omitted ...] and build integrations, data pipelines, and platform capabilities across clinical data platforms, APIs, identity boundaries, and legacy enterprise systems. Architect and evaluate production AI systems that combine frontier models, context engineering, retrieval, tool use, orchestration, data platforms, and deterministic services. Stay deeply hands-on in code and infrastructure, solving difficult integration, data, reliability, and production-platform problems. Drive delivery across both organisations, resolving technical disagreements, dependencies, and risks. Communicate architecture, progress, trade-offs, risks, and results clearly to audiences ranging from implementation tea