Software Engineer, Dev Velocity (all levels)

Render is building a modern cloud platform for developers creating AI-native, full-stack, multi-service applications. The Software Engineer on Developer Velocity will design and build internal platforms, tooling, and automation that improve engineering velocity, including local development environments, CI/CD pipelines, test infrastructure, and engineering productivity metrics.

Responsibilities:

• Improve speed and reliability of early change feedback
• Invest in build and dependency tooling, caching, incremental builds, and monorepo ergonomics, to keep iteration tight as the codebase grows
• Accelerate our CI/CD pipelines - cutting build, test, and deploy times while keeping the path to production safe and reversible
• Make our test suites fast and trustworthy: parallelization, smart test selection, flaky-test detection, and better local/preview environments built on the same primitives our customers use
• Design and build tools to support concurrent agent execution
• Make test feedback fast enough to live inside an agent's loop, where slow or flaky runs compound across every attempt
• Get agents the right context (codebase conventions, service ownership, recent changes, environment state) so their first attempt lands closer to correct
• Simplify and establish repeatable patterns
• Reduce toil through automation, paving over repetitive workflows and manual steps wherever they slow people down
• Instrument the engineering org with meaningful signals (deployment frequency, lead time for changes, change failure rate, time to restore) and turn them into action
• Build and participate in an on-call rotation as the team takes ownership of critical systems

Requirements:

• • Experience building and operating developer-facing tooling, CI/CD systems, or internal platforms that other engineers depend on every day
• • Experience driving cultural and process changes to make engineering teams more effective
• • Strong software engineering fundamentals and a track record of shipping, maintaining, and debugging production systems
• • Proficiency in Go (or a strong willingness to ramp quickly, it's our primary language)
• • Hands-on experience with Kubernetes or similar container orchestration
• • Familiarity with infrastructure-as-code tools (yup, Terraform)
• • A bias toward measurement: you instrument what you build and let data tell you whether you actually made things faster
• • You empathize deeply with engineers, fixing developer pain points in an elegant and sustainable manner is something that resonates deeply with you
• • Experience improving build systems, test infrastructure, or developer experience at meaningful scale - Bazel, Concourse, and GitHub workflows are old friends
• • Familiarity with observability tools like Datadog, Grafana, and OpenTelemetry
• • Comfort working close to the metal - Linux, containers, kubernetes - you get your hands •very• dirty
• • Security-minded instincts, especially around supply chain and the path from commit to deploy
• • Understanding that the question isn't "AI pilled vs AI skeptic", but rather where to use it as an accelerant, and where human context must come first