Senior Backend Engineer (AI), Pipeline Execution

GitLab is the intelligent orchestration platform for DevSecOps, enabling organizations to increase developer productivity and improve operational efficiency. In this role, you will help shape and scale the core infrastructure behind GitLab CI, integrating AI into CI/CD workflows and designing AI-assisted experiences.

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

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
• 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