Head of Engineering [NYC or SF]

About Amigo At Amigo, we're building the clinical AI infrastructure that health systems, life sciences companies, payors, and government agencies run their patient-facing care on. Our agents work across the whole patient journey: pre-visit intake, care navigation, post-visit care plans, and ongoing monitoring. Our mission is to make excellent care accessible to every patient, not rationed by the limits of clinician time. This hasn’t been solved because the underlying record was never built for it. EHRs were designed for billing, not for systems that learn. So instead of layering another point solution on top, we’re rebuilding the medical record as a timeline of clinical events and running agents on top of it that improve with every patient interaction. Unlike single-purpose chatbots or scribes, Amigo is the platform our customers use to build their own agents. That means our work has to hold up across specialties, workflows, and regulatory environments and not just one narrow use case. Our agents have supported more than 4 million patient encounters and are on track to grow tenfold this year. Our work is validated through partnerships with leading academic medical institutions. We’re fresh off our Series A, backed by Tier 1 VCs such as Madrona, General Catalyst, and Optum Ventures. We’re a small team of around 35 people, working in person in New York City and San Francisco. [... source excerpt omitted ...] gment. You’ll work closely with our CTO on technical strategy and partner with the Applied AI and Forward Deployed teams whose deployments depend on the platform, translating what customers actually need into systems that hold up. The ideal candidate brings a strong engineering background, a deep sense of ownership, and the ability to build an organization rather than simply run one. What you'll do Lead and grow engineering across application, backend and infrastructure, and data, supporting engineers with mentorship, direct feedback, and clear technical guidance Hire engineers and develop leaders, building a team that continuously raises its own bar Drive execution from prob [... source excerpt omitted ...] g system design and helping the team navigate architectural tradeoffs Set the engineering culture: how we review code, how we ship, what we consider done, and how we respond when production issues arise Break large platform problems into increments that deliver value early while still supporting the platform’s long-term direction Partner with the Applied AI, Forward Deployed, and product teams to align priorities and decide what the platform should absorb versus what remains bespoke per customer Keep the team fluent in the reliability, security, and privacy implications of what they build in an environment involving patient data What we're looking for A track record of engine