Staff Software Engineer - Developer Experience & Ai Enablement

About Us:

Grow was born to tackle a critical challenge: making mental health care more effective and accessible for everyone. Since launching in 2020, 15 million sessions have started on Grow, and we've barely scratched the surface. We do it through a three-sided marketplace that empowers providers, augments insurance payors, and serves patients. Every solution we build reveals ten more waiting to be delivered, and that's just what gets us going. We've backed that ambition with more than $328M in funding, including our Series D at a $3B valuation from Sequoia Capital, Transformation Capital, TCV, SignalFire, Menlo Ventures, Goldman Sachs Alternatives, and others.

At Grow, the work you do can literally change someone's life. Your work here doesn't stay on a screen; it impacts whether someone can find, afford, and access quality care. That ambition sets us apart, and offers you an endless runway to impact one of the world's most urgent issues. We don’t have passenger seats here. Everyone is driving something that matters.

This work deserves real commitment. So if you thrive on meeting problems head on, untangling serious complexity, and working at pace with the sharpest yet kindest people around, you've come to the right place.

The Opportunity:

Grow Therapy's Developer Experience team exists to make our ~120 engineers (and growing) measurably faster and happier. We treat developer tools as a product: our customers are engineers, and everything we ship, from CI/CD and test infrastructure to build tooling and AI-native development workflows, is judged by whether it makes their day better.

We are looking for a Staff Software Engineer to set technical direction for this work across the engineering organization. The team is small, fully senior, and largely greenfield: the goals are set at the org level and tracked by our most senior technology leaders, but the project list is yours to discover. Today, improvements to how teams build, test, and review code live in pockets. The staff engineer on this team turns pockets into paved roads: identifying the bottlenecks that cost every engineer time, designing the standard, and driving adoption across teams that do not report to you.

This is a hands-on role on an AI-forward team. We are actively building agentic developer workflows and expect AI to be the primary lever in how we climb from AI-assisted to AI-native development.

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 think about developer tools with a product mindset, measuring adoption and developer satisfaction rather than shipping and hoping

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

Bonus: 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.