Staff Backend Engineer (AI), Verify

GitLab
Full-timeStaff
Visa Sponsorship

AI Tools

AI AgentsAgentic CIDuo Agent Platform

Tech Stack

RubyRuby on RailsPostgreSQLLLMs

Agent Workflow

Design and implement AI-powered features for Agentic CI, including agents, agentic flows, and LLM-backed tooling that integrates with GitLab's Duo Agent Platform. AI Pipeline Builder auto-creates pipelines. Fix a Failing Pipeline automates troubleshooting at scale.

About the Role

GitLab seeks a Staff Backend Engineer to shape and scale the core infrastructure behind GitLab CI while integrating AI into CI/CD workflows. The position emphasizes defining success metrics for AI-assisted features and building observability layers for production systems.

Key Responsibilities:

  • Shape and scale GitLab CI backend infrastructure for performance and reliability
  • Design and implement AI-powered features for Agentic CI, including agents, agentic flows, and LLM-backed tooling that integrates with GitLab's Duo Agent Platform
  • Define measurable success criteria before building features
  • Build instrumentation and observability dashboards for AI-assisted CI
  • Drive performance improvements through data-driven experimentation
  • Write secure, maintainable Ruby on Rails code in a large monolith
  • Lead cross-functional technical work with Product, UX, and Infrastructure teams
  • Share standards and patterns for responsible AI integration across the organization

Required Qualifications:

  • Advanced proficiency with Ruby and Ruby on Rails
  • Strong PostgreSQL skills (data modeling, query tuning, scaling)
  • Hands-on high-traffic production systems experience
  • Practical experience designing and shipping AI-powered backend features
  • Data-driven engineering approach with hypothesis testing
  • Observability patterns and tools familiarity
  • Backend architecture expertise with secure design practices

Agentic CI features include:

  • AI Pipeline Builder: Auto-creates pipelines for new projects
  • Fix a Failing Pipeline: Automates pipeline troubleshooting at scale
  • LLM-backed tooling integration
  • Building safeguards and cost controls for AI-driven automation
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