Staff Backend Engineer, AI Verify

Overview of the Staff Backend Engineer, AI Verify Role at GitLab

As a Staff Backend Engineer, AI Verify at GitLab, you will play a pivotal role in shaping and scaling the core infrastructure behind GitLab CI. You will be central to integrating AI into CI/CD workflows, directly impacting the performance, reliability, and usability for millions of users, from small teams to large enterprises.

AI is a top strategic priority for GitLab. In this role, you will be instrumental in designing, building, and iterating on AI-assisted and agentic CI experiences. This includes setting standards for the AI agent portfolio, defining success metrics, instrumenting behavior in production, and accounting for large language model limitations. You will also be responsible for the responsible integration of GitLab's Duo Agent Platform into CI workflows at scale, ensuring a foundation that is fast, reliable, secure, and observable.

Key Responsibilities and Goals

We have ambitious goals for Agentic CI in the upcoming fiscal year. As a Staff Backend Engineer, AI Verify, you will:

• Partner with Engineering, Product, and UX leadership to critically evaluate priorities, identify areas for accelerated development, pinpoint data gaps, and discover innovation opportunities. This involves continuous learning and growth with your collaborative engineering team.
• Define clear success metrics across our agent portfolio, ensuring we track progress beyond mere shipping to prioritize continuous learning and improvement.
• Maintain a keen awareness of the competitive landscape to ensure GitLab CI remains best-in-class in an evolving agentic world.

Examples of Agentic CI Work

Anticipated work for the upcoming year includes:

• Developing the AI Pipeline Builder, a foundational CI agent designed to auto-create pipelines for new projects and streamline onboarding for new CI users.
• Automating the "Fix a Failing Pipeline" flow at scale, from internal dogfooding on GitLab projects to safe, controlled rollouts for customers, addressing significant infrastructure and scalability challenges.
• Building a robust instrumentation and observability layer for agentic CI, including trigger volume dashboards, retry rates, and cost safeguards, to enable confident measurement, issue detection, and iteration.
• Hardening the CI pipeline execution infrastructure (database access patterns, background processing, job orchestration) to accommodate the increased load introduced by AI-driven automation at enterprise scale.

What You'll Do

• Shape and scale GitLab CI backend infrastructure to enhance performance, reliability, and usability for high-volume job execution.
• Design and implement AI-powered features for Agentic CI, including agents, agentic flows, and LLM-backed tooling integrated with GitLab's Duo Agent Platform.
• Define clear success metrics for AI in CI before development, establishing baselines, measurable outcomes, and signals for team learning and iteration.
• Build necessary instrumentation and observability for trustworthy AI-assisted CI in production, covering feature behavior metrics, dashboards, and safeguards.
• Drive measurable performance improvements across CI systems (e.g., database access, background processing, job orchestration) through hypothesis testing, experiments, and data validation.
• Write secure, well-tested, maintainable Ruby on Rails code within a large monolith, improving existing features and reducing technical debt and operational risk.
• Lead cross-functional technical initiatives with Product, UX, and Infrastructure, influencing architecture and execution within the Verify stage.
• Share best practices, patterns, and insights with fellow engineers, elevating standards for responsible AI integration and evidence-driven engineering across CI.

What You'll Bring

• Advanced proficiency with Ruby and Ruby on Rails, including experience building and maintaining reliable backend services in large codebases.
• Strong PostgreSQL skills, encompassing data modeling, query tuning, and scaling large tables through proactive performance investigation.
• Hands-on experience building, running, and debugging high-traffic production systems, particularly in CI, workflow orchestration, or similar infrastructure-heavy domains.
• Practical experience designing and deploying AI-powered backend features and integrations, demonstrating sound judgment regarding large language model limitations and responsible production use.
• A data-driven engineering approach: forming hypotheses, establishing baselines, instrumenting changes, and measuring outcomes against clear success criteria.
• Familiarity with observability patterns and tools (metrics, logging, tracing) for issue diagnosis, reliability improvement, and iterative development.
• Strong backend architecture and delivery practices, including secure design, well-tested code, and strategies for safe rollouts and zero-downtime changes.
• Clear written and verbal communication skills, crucial for technical proposals, documentation, and effective collaboration in a remote, asynchronous, cross-functional environment.

About The Verify Team

The Verify stage at GitLab focuses on collaboration, iteration, and empowering users to run fast, reliable, and scalable Continuous Integration (CI) pipelines for projects of all sizes. Learn more about our ways of working on the Team Handbook Page and Related Initiative.

How GitLab Supports You

• Benefits covering health, finances, and well-being.
• Flexible Paid Time Off.
• Team Member Resource Groups.
• Equity Compensation & Employee Stock Purchase Plan.
• Growth and Development Fund.
• Parental leave.
• Home office support.

Key skills/competency

• Ruby on Rails
• PostgreSQL
• Backend Engineering
• AI Integration
• CI/CD Workflows
• System Scalability
• Observability
• Large Language Models (LLM)
• Data-Driven Engineering
• Technical Leadership