Member of Technical Staff

Category-defining tech. Career-defining work.

Lots of tech companies disrupt. But, many fail when they try to scale. We're different. CockroachDB makes it easier for companies to build and scale apps. This is how and why we're helping some of the most innovative companies on the planet. We tackle problems head-on and focus on solutions that create lasting impact.

Because when our customers win, we all win.

Cockroach Labs is looking for a software engineer to join Code Systems, part of our Engineering Productivity organization based in India. Code Systems builds and operates roachdev, CRL's unified infrastructure for running coding agents and automating engineering workflows across the company - from an engineer's laptop, to worker VMs, to stateless cloud agents triggered by GitHub, Slack, and Mica.

This role has shifted from a traditional DevOps/developer-infrastructure profile to one centered on general software engineering and applied AI. You'll spend most of your time building and hardening AI-powered developer tools - building AI automated code review, CI failure triage, and agentic automation - rather than just managing build systems or CI infrastructure in isolation. You'll still need working knowledge of CI/CD and developer workflows, but the emphasis is on shipping product-quality software that happens to serve engineers as its customers.

Success in this role means designing and building reliable, observable systems that put AI agents safely in the loop of everyday engineering work, and collaborating closely with engineering teams across CRL to roll them out.

Our team values

• Providing high-quality support to Cockroach Labs engineering teams and a strong desire to help other people work more productively.

• Engaging with other Cockroach Labs engineers to build relationships, listen to developer pain points, and identify opportunities to apply AI and automation to real workflows.

• Minimizing and automating away toil - including the toil of using AI safely and reliably.

• Shipping incrementally, measuring quality with real data, and being honest about where AI tooling still needs a human in the loop.

Some examples of work the team is doing

• Building roachdev's AI code review pipeline - migrating CRL's major repositories (cockroach, pebble, managed-service) off third-party review tools (BugBot, GitHub Copilot, Claude Code Action) onto our own AI-driven PR review system.

• Adding observability to AI review: surfacing findings, confidence scores, and token/cost metrics as build artifacts, backed by an event gateway that routes GitHub webhooks through Pub/Sub and a metrics pipeline for quality