Write and ship production code weekly—you'll be in the codebase alongside your team
Drive a culture of shipping speed and continuous improvement—identify bottlenecks, reduce cycle times, and treat fast iteration as the primary mechanism for achieving quality in a regulated environment
Build internal tools that give clinical and operations users visibility into AI decision-making, with appropriate guardrails, permissions, and correction workflows
Work closely with an embedded AI engineer who owns prediction model quality, while you own the production systems, user-facing workflows, and speed gains that depend on those predictions
Lead incident response and postmortems for team-owned systems; ensure failures result in durable fixes, not patches
Mentor 3 engineers through building together—pairing, code review, and architectural decisions made in the context of real work
Establish and maintain system reliability standards: monitoring, alerting, and continuous improvement loops that catch problems before users do

7+ years of software engineering experience, including 2+ years managing engineers while staying deeply hands-on—you've continued to ship production code as a manager
Owned production systems processing large volumes of unstructured or semi-structured data, with personal accountability for reliability and correctness
Meaningful experience building and operating AI-powered systems in production—you understand what it takes to make AI work reliably at scale, not just call an API
Built internal tools or platforms for non-technical or regulated users, with demonstrated sensitivity to trust, UX, and workflow fit
Comfortable making high-stakes technical decisions with incomplete information—and accountable for the outcomes, including failures
Operated in ambiguous environments where requirements evolve, tradeoffs are real, and you're expected to drive clarity rather than wait for it
Strong opinions on system observability, debugging, and operational excellence
A track record of integrating AI into your engineering practices and workflows—not just the product you build, but how you build it. You have a point of view on how AI development agents are changing software engineering and ideas for how to stay ahead of that curve at PicnicHealth.

Engineering Manager – Capture

Key skills