Senior Backend Engineer (AI), Pipeline Execution

GitLab

2h•Remote

About The Position

GitLab is the intelligent orchestration platform for DevSecOps. GitLab 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 GitLab 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. GitLab 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. As a Senior Backend Engineer (AI) in the Verify stage at GitLab, you'll help shape and scale the core infrastructure behind GitLab 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 GitLab's Duo Agent Platform into CI workflows at scale, on a foundation that's fast, reliable, secure, and observable.

Requirements

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 Haves

Experience with AI agents or agentic frameworks (for example, LangChain or similar technologies) and building agentic workflows in production environments.
Strong PostgreSQL skills, including data modeling, query tuning, and scaling large tables through proactive performance investigation and remediation.

Responsibilities

Collaborate with Engineering, Product, and UX partners to refine priorities: where we can move faster, where we’re missing data, and where there’s whitespace to innovate.
Contribute to defining what success looks like across our AI agents, ensuring we’re not just shipping, but learning from how features perform in production.
Keep a close eye on the competitive landscape and emerging AI-native DevOps tools, helping us understand what it takes to keep GitLab CI best-in-class in an increasingly agentic world.
Design, build, and operate backend features that make GitLab CI fast, reliable, and easy to use at scale.
Implement AI-powered and agentic CI capabilities that integrate with GitLab’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.