Staff Software Engineer, Developer Infrastructure (Test Infrastructure)

's Developer Infrastructure - Test team exists for one reason: every engineer should get fast, reliable test signals so the company can test and ship faster. As AI accelerates the pace of code generation, test infrastructure is becoming a critical path for how quickly delivers value to customers. As a Staff Software Engineer on the Platform team, you'll set the technical direction for how tests and ships software, owning the systems that turn testing into a speed advantage instead of a bottleneck.

What you'll do:

• Define and own the technical strategy for test infrastructure across engineering, with feedback speed as a core design constraint.
• Build and operate core test infrastructure services, including test orchestration, smart test selection, sharding, flaky-test detection, and test result analysis.
• Drive measurable improvements in test feedback speed and signal reliability so engineers can ship with confidence and without reruns.
• Own systems end to end, including architecture, observability, SLOs, and on-call operations.
• Partner with engineering teams across to identify bottlenecks and turn them into platform improvements.
• Mentor engineers, raise technical standards, and shape how the organization approaches test infrastructure.

Required Skills and Experience:

• 10+ years building and operating production software, with distributed systems fundamentals and proficiency in Go or a similar language.
• Track record of defining and delivering technical strategy for foundational systems that other teams depend on.
• Deep experience in test infrastructure, including test execution at scale, flaky-test detection, test selection and its tradeoffs between speed and coverage, sharding, or test result analysis.
• Proven experience operating reliable systems at scale using Kubernetes, AWS, GitHub Actions, Terraform, containers, and observability tooling such as Datadog.
• Demonstrated success measuring platform impact through developer adoption and workflow improvements, with experience building and maintaining SLOs and incident response processes.
• Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality.