About this role
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
The Community You Will Join:
Airbnb is a mission-driven company dedicated to helping create a world where anyone can belong anywhere. It takes a unified team committed to our core values to achieve this goal. Airbnb's various functions embody the company's innovative spirit and our fast-moving team is committed to leading as a 21st century company.
The Difference You Will Make:
The Service Tools team's mission is to enable Airbnb backend developers to develop, test, and maintain their code quickly and reliably. We own the standard development lifecycle for service owners — from AI-assisted development, through the build system, integration testing and code review, to how services get built for deployment. This represents Airbnb's largest cohort of developers, and you will ultimately be responsible for their productivity.
As a Staff Engineer, you will set technical direction rather than only deliver against it. You will own a platform-spanning area of the developer lifecycle end to end — framing the problem, building the measurement that proves it matters, driving a roadmap with partner teams across the company, and growing the engineers who build it with you. The next 18–24 months of this platform are genuinely open: agentic development is changing what the inner loop looks like, and we want someone who wants to help decide what it should become.
A Typical Day:
• Owning a multi-quarter, platform-spanning workstream — agentic developer workflows, intelligent build infrastructure, test excellence, codebase modernization, or developer observability — as the DRI other teams come to
• Advancing our AI-assisted development platform: agent skills and tool integrations, the evaluation harnesses that keep them honest, and the telemetry that shows where a human still has to intervene
• Scaling build and merge infrastructure for a very large JVM monorepo: Bazel, remote build execution and caching, merge-queue throughput, test sharding and selection, and the capacity modeling that keeps it all inside budget
• Raising the floor on testing — coverage and mutation signal, AI-authored tests, faster local and pre-merge feedback, and testing contracts teams can hold each other to
• Leading large-scale codebase modernization (JDK and Kotlin toolchain upgrades, test-framework migrations, build-module migrations) through automated refactoring rather than manual toil
• Turning developer and production telemetry into decisions — quantifying where time, spend, and confidence are being lost, and using that to change priorities, including your own team's
• Setting standards by example: code and archi