Senior Backend Engineer (AI), Pipeline Execution

An overview of this role

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.

In this role, you will:

• 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.

Examples of Agentic CI work we have planned for the upcoming year:

• 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 GitLab 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.

What you’ll do:

• 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.

What you’ll bring:

• 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, 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.

An overview of this role

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.

In this role, you will:

• 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.

Examples of Agentic CI work we have planned for the upcoming year:

• 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 GitLab 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.

What you’ll do:

• 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.

What you’ll bring:

• 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, 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.