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- GitLab
- Staff Backend Engineer (AI), Verify
Staff Backend Engineer (AI), Verify
Full-timeStaff
Visa SponsorshipAI 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