Staff Forward Deployed Engineer

Role overview

Join GitLab’s Forward Deployed Engineering team as a Staff Forward Deployed Engineer. You’ll focus on strategic customer outcomes and AI adoption, while also contributing directly to GitLab’s core product.

Missions / key responsibilities

• Diagnose and resolve high-impact adoption blockers with strategic customers
• Collaborate with Product, Engineering, Support, and other teams to translate field-discovered issues into durable product improvements
• Contribute production-grade fixes and features to GitLab
• Develop reusable adoption models to support AI integration and improve customer workflows
• Operate at the intersection of customer urgency, technical ambiguity, and product execution

Requirements

• Staff-level product or platform engineering experience
• Strong experience with Ruby/Rails and Go (and ability to contribute to GitLab directly)
• Deep understanding of modern DevSecOps workflows, including:
  • Git, merge requests, CI/CD, security controls, compliance needs, enterprise delivery
• Ability to diagnose complex behavior across:
  • Application code, data stores, infrastructure, observability, networking, APIs, and customer usage patterns
• Demonstrated ability to contribute to large, mature production codebases with strong standards for:
  • testing, maintainability, performance, and security
• Strong written communication skills (technical narratives, architecture guidance, reusable assets)
• Experience working with strategic customers / senior technical stakeholders in ambiguous, high-impact situations
• Ability to coordinate across many internal teams without formal authority
• Experience with GitLab as a platform (GitLab.com, Dedicated, or self-managed)

Nice to have / additional capabilities

• Production experience with: PostgreSQL, Redis, Sidekiq, Vue, TypeScript, Kubernetes, Docker, Linux, and observability tooling
• Familiarity with Git internals / large-scale Git usage or CI runner behavior
• AI adoption experience (AI-assisted development, agentic workflows, AI governance, model evaluation, context management, prompt/workflow design) especially in regulated enterprise environments
• Experience producing thought leadership (whitepapers, talks, RFCs, technical writing, internal strategy documents)
• Background in performance engineering, SRE/platform/infrastructure, or distributed systems
• Experience in open-source or highly asynchronous engineering environments

How you’ll work

You’re comfortable operating “field-capable” without being field-only: reading traces, writing production code, debugging architecture, discussing AI governance, leading technical sessions, opening merge requests, and coordinating internally to drive customer outcomes.