Ship production code across the stack. You do not need to be a specialist in every layer, but you should be comfortable contributing wherever the work demands it.
Set the bar for AI-native engineering across the pod. Effectively leverage AI tools and workflows deeply in your own work and establish a higher standard for speed, depth, quality, and leverage than the team has today.
Raise the technical bar through strong design instincts, substantive code review, and sound architectural judgment.
Make pragmatic technical decisions that reduce rework, improve maintainability, and keep the team moving with high quality.
Raise the pod’s execution standard across planning, work breakdown, prioritization, unblocking, and delivery.
Partner closely with product on roadmap planning, execution, tradeoffs, and sequencing, bringing clarity and engineering judgment rather than passive delivery management.
Coach and develop engineers through direct, timely, actionable feedback against a clear performance bar.
Build a high-clarity, high-accountability team environment where people know what excellence looks like, where they stand, and what needs to improve.

4+ years of people management experience, including hiring and driving performance.
Recent hands-on engineering experience.
A track record of raising engineering standards across code quality, review rigor, testing discipline, and architecture.
Fluency with AI-augmented development workflows. You use tools like Claude Code, Codex, Cursor, or similar as part of your real day-to-day workflow.
High standards for code quality, product craft, and execution.
Clear, direct communication. You give feedback promptly, set a high bar, and follow through.
The ability to inherit a team, quickly form an accurate read, and raise the standard without creating unnecessary drag.

Engineering Manager

Key skills