Staff Software Engineer, Developer Infrastructure (Test Infrastructure)

Coinbase is a financial technology company focused on increasing economic freedom through cryptocurrency and financial infrastructure. The Staff Software Engineer will set the technical direction for developer test infrastructure, build and operate systems for test orchestration and analysis, improve feedback speed and reliability, and mentor engineers across the organization.

Responsibilities:

• Define and own the technical strategy for test infrastructure across Coinbase 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 Coinbase to identify bottlenecks and turn them into platform improvements
• Mentor engineers, raise technical standards, and shape how the organization approaches test infrastructure

Requirements:

• 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