What we're looking for
We're looking for a Staff Engineer to own the technical quality bar for the team. We're at the point where the decisions we make now determine what the next three years cost us: our platform spans real-time voice AI, agentic systems, a web application our team lives in all day, and integrations that carry both patient care and revenue — all moving fast, all built by a small team.
You'd own the view across all of it. That means the architecture and the build-versus-buy calls, where we invest in reliability and where we take on debt deliberately. It also means the engineering harness — the tooling, guardrails, and automation that let people ship in parallel without breaking each other's work, and that let non-engineers ship safely too, with AI doing the work and the system catching the mistakes. And it means being the bar raiser: the engineer whose review makes the work better and whose standards the team adopts and keeps.
This is a hands-on role. You'll write code and review a lot of it, set the standards for testing, observability, security, and deploys, and then be the one who holds the line on them. Like every engineer here, you'll also own business outcomes: take a company goal, find where the leverage is, turn it into a roadmap, ship, and measure whether it moved the number.
The archetype we have in mind: a deep backend or full-stack engineer who has built systems that held up under real load and real consequences, and who is now genuinely comfortable with AI/ML engineering. The mirror image works just as well — a strong ML engineer whose software engineering depth is equally real. Either way, you've led teams before and raised the bar on them.
Qualifications
- Staff-level experience as a backend or full-stack engineer, with a track record of owning systems that mattered — high traffic, high stakes, or both.
- Real depth in AI/ML engineering. You've built and operated LLM-powered or ML systems in production and can reason about their failure modes, evaluation, cost, and latency as fluently as you reason about a database.
- You've made architectural decisions at scale and lived with the consequences. You can talk concretely about a call you got right and one you got wrong.
- Strong judgment on build vs. buy, on when to invest in infrastructure versus ship the simple thing, and on how much rigor a given system deserves.
- You've set and enforced engineering standards on a team, in a way that made people faster rather than slower.
- You're passionate about being on the cutting edge of software engineering. Best practices are changing fast right now, and you're the person who tracks what's actually working and brings it to the team.
- You've led a team and been its bar raiser, whether or not you carried the manager title.
- You're hands-on. You still write and review code, and you'd be unhappy if you couldn't.
- You have product judgment, and can show it: a time you challenged a spec, cut scope to ship what mattered, changed course after watching real users, or built something nobody asked for that turned out to matter.
Strong ML engineering backgrounds are equally welcome, provided the software engineering depth is there too. We care that both halves are real.