Engineering Manager, Product

Doctronic•San Francisco, CA

1d•$200,000 - $300,000•Hybrid

About The Position

Doctronic is hiring an Engineering Manager to lead a team building its products and underlying AI systems. This hands-on management role combines people leadership with active technical contribution: developing engineers, shaping technical direction, translating ambiguous product needs into reliable production software, and remaining accountable for team health, technical quality, delivery, and product impact. The manager works in the codebase, guides architecture, reviews changes, investigates production issues, and ships alongside the team. Engineering leaders are expected to use coding agents as part of daily work and to direct, validate, and improve their use while remaining responsible for the correctness of shipped software. The manager partners with product, design, clinical, AI, and operations teams to prioritize problems and define success. The role spans user experiences, backend services, data models, integrations, and AI workflows, including the design of useful AI product behavior, reliable orchestration, safeguards, and real-world evaluations. The manager also owns the operation of the team’s services, works with Platform on shared infrastructure and standards, and uses product usage, user feedback, AI evaluations, and production performance to inform ongoing improvements. Doctronic’s production stack includes a Next.js, React, and TypeScript web application; native iOS and Android applications built with Swift and Kotlin; and Python and FastAPI services. Backend systems use MariaDB, SQLAlchemy, Redis, and Celery. Services run in Docker on AWS ECS and integrate with AI providers, telehealth systems, healthcare APIs, and FHIR-based workflows. Experience with every component is not required, but the manager should be comfortable learning unfamiliar systems and contributing across product and backend code. The team is small, senior, and autonomous. Teams own projects from definition through launch, iteration, and production support, with short planning cycles and frequent releases. High standards apply to patient safety, privacy, reliability, and code quality. The role is hybrid in New York City or San Francisco, with a base salary of $200,000 to $300,000 plus equity.

Requirements

Experience managing and developing engineers who build and operate user-facing products or the systems behind them.
Strong software engineering background and current ability to contribute production code and work through difficult technical problems.
Experience shipping across frontend and backend systems, with depth in at least one area and the ability to lead work across the rest.
Good product judgment: ability to clarify problems, challenge assumptions, choose appropriate scope, and connect engineering decisions to user outcomes.
Daily experience directing coding agents and evidence of improving how a team builds software with them.
Practical judgment about AI systems, including where to use models and agents, how to evaluate their behavior, and where explicit controls and human judgment are needed.
Record of improving engineering throughput while maintaining quality, reliability, and maintainability.
Experience hiring, coaching, giving direct feedback, and helping engineers grow.
Sound decisions about patient safety, privacy, security, accessibility, and production reliability.
Clear communication across engineering and company leadership, including explaining tradeoffs and surfacing risks early.
Comfort learning unfamiliar systems and contributing across product and backend code.

Nice To Haves

Experience with AI products, agent orchestration, or evaluation systems.
Experience in healthcare or another regulated field.

Responsibilities

Lead and grow a team of product engineers through clear expectations, coaching, direct feedback, and high standards.
Partner with product, design, clinical, AI, and operations teams to understand problems, set priorities, and define success.
Turn incomplete requirements into focused projects, make technical tradeoffs, and keep the team shipping through short planning cycles.
Contribute production code, lead technical investigations, review changes, and help resolve difficult implementation and production problems.
Guide work across user experiences, backend services, data models, integrations, and AI workflows, helping engineers own complete solutions across those boundaries.
Turn AI capabilities into useful product behavior with clear interfaces, reliable orchestration, appropriate safeguards, and evaluations that reflect real use.
Make coding agents and automation effective across the team by improving work scoping, context, verification, and reusable tooling.
Own the operation of the services the team ships, partnering with Platform on shared infrastructure, tooling, and standards.
Review product usage, user feedback, AI evaluations, and production performance after launch, and use findings to improve the product and team decisions.
Hire strong engineers and build a team able to take on broader scope as Doctronic grows.