Senior Backend Engineer; AI), Pipeline Execution

Git Lab is the intelligent orchestration platform for Dev Sec Ops . Git Lab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100 trust Git Lab to ship better, more secure software faster.

The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. Git Lab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems.

Co-create the future with us as we build technology that transforms how the world develops software.

An Overview Of This Role

As a Senior Backend Engineer (AI) in the Verify stage at Git Lab, you'll help shape and scale the core infrastructure behind Git Lab CI. You'll play a key role in how we integrate AI into CI/CD workflows, working on features that improve performance, reliability, and usability for people running millions of CI jobs, from small teams to the largest enterprises.

AI is a top priority in the year ahead. In this role, you'll go beyond using AI tools — you’ll design, build, and iterate on AI-assisted and agentic CI experiences. You’ll help define and implement patterns for how we measure success, how we instrument behavior in production, and how we account for large language model limitations in real-world environments. You'll also help integrate Git Lab's Duo Agent Platform into CI workflows at scale, on a foundation that's fast, reliable, secure, and observable.

• Design, build, and operate backend features that make Git Lab CI fast, reliable, and easy to use at scale.
• Implement AI-powered and agentic CI capabilities that integrate with Git Lab’s Duo Agent Platform.
• Instrument, monitor, and improve CI systems using data, observability, and safe rollout practices.
• Write secure, well-tested Ruby on Rails code in our monolith, improving existing features while reducing technical debt.
• Collaborate cross-functionally with Product, UX, and Infrastructure, mentoring others and raising engineering standards across the Verify stage.

• AI Pipeline Builder, the foundational CI agent that auto-creates pipelines for new projects and serves as the launchpad for onboarding new CI users.
• Automate the Fix a Failing Pipeline flow at scale – from dogfooding on internal Git Lab projects through to safe, controlled rollout for customers, solving real infrastructure and scalability challenges.
• Build the instrumentation and observability layer that makes agentic CI trustworthy — trigger volume dashboards, retry rates, cost safeguards — so we can measure what’s working, catch what isn’t, and iterate with confidence.
• Harden the CI pipeline execution infrastructure that these agents depend on: database access patterns, background processing, and job orchestration built to handle the additional load that AI-driven automation introduces at enterprise scale.

• Strong Ruby on Rails backend experience in a large, production codebase.
• In-depth experience building and operating AI-powered backend features in production.
• A data- and observability-driven approach to diagnosing issues, improving reliability, and validating impact.
• Clear written and verbal communication, with a collaborative, mentoring mindset in a remote, async environment.
• Hands-on experience building, running, and debugging high-traffic production systems, ideally in CI, workflow orchestration, or adjacent infrastructure-heavy domains. Nice to have
• Experience with AI agents or agentic frameworks (for example, Lang Chain or similar technologies) and building agentic workflows in production environments.
• Strong Postgre
  
  SQL skills, including data modeling,…