Staff Software Engineer

What You'll Be Doing

• Own the highest-leverage developer-experience problems across engineering end to end, deciding which bottleneck is worth solving, designing the approach, and driving org-wide adoption.
• Set and evolve engineering-wide standards for how teams build, test, and ship, and do the alignment work to make them stick as the org grows.
• Making our large codebase fast to work in: build systems and monorepo tooling, CI/CD pipeline performance, test reliability and framework strategy.
• Set the golden paths for how engineers work with AI, find the highest-leverage places to push it deeper into the development loop, and keep Grow at the front of a fast-moving space.
• Drive the technical strategy for breaking up the monolith, from the incremental migration path to the test-isolation and build tooling that makes it possible at scale.
• Embedding with product teams to understand their workflows firsthand, and treating their feedback as product input.
• Raising the bar for the engineers around you through design review, mentorship, and the quality of your own shipped work.

You'll Be a Good Fit If

• You have deep developer experience, developer productivity, or platform engineering experience where internal engineers were your customer, or you built developer tools as the product at a developer-tools company.
• You have owned problems that only exist at scale: monorepo tooling, build systems (Bazel or similar), CI performance for large test suites, or test framework migrations, and you can speak to the before-and-after outcomes.
• You think about developer tools with a product mindset, defining what success looks like up front and measuring adoption and developer satisfaction to know you've delivered it.
• You are genuinely excited about AI development tooling and have opinions grounded in things you have built.

Bonus

• Python ecosystem depth, GitHub Actions at scale, or prior experience driving standards across a 100+ engineer organization.
• You've built developer-facing AI tooling - coding agents, AI code review, LLM developer workflows, MCP - and have a grounded view of where it does and doesn't help.