Head of Engineering [NYC of SF]

Amigo•San Francisco, CA

4d•$300,000 - $500,000•Onsite

About The Position

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. We care deeply about craft, clinical rigor, and the speed at which good ideas reach patients. If you want your work to be measured in outcomes rather than releases, we’d like to hear from you.

Requirements

A track record of engineering leadership in organizations with a strong engineering culture.
Breadth across more than one of application, backend and infrastructure, and data platform. This role spans all three, so we're looking for a generalist leader rather than a specialist in one area
Experience managing and developing engineers, including hiring, mentorship, and performance conversations, with examples of people who grew under you
A strong technical background, and enough current depth to engage credibly in system design, architecture, and tradeoff decisions
The ability to translate customer needs and engineering goals into a roadmap and then into shipped systems
Excellent communication across engineering, product, and the customer-facing teams, including the judgment to know when to escalate and when to absorb
A deep sense of ownership for both team outcomes and long-term system health
Comfort with ambiguity. Priorities move as deployments teach us what customers actually need
Healthcare experience is not required. Strong engineering leadership transfers, and the clinical context is learnable

Nice To Haves

Experience leading engineering inside a data-heavy company, or owning a data platform alongside application and backend teams
Background in highly scalable distributed systems or infrastructure platforms
Experience building platforms or products consumed directly by other engineers
Familiarity with regulated environments, whether healthcare, financial services, or the public sector

Responsibilities

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 problem definition through deployment, balancing speed with the reliability a clinical setting demands
Engage deeply in technical discussions, guiding 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