Distinguished Engineer, Core DevOps

GitLab is an intelligent orchestration platform for DevSecOps. The Distinguished Engineer will lead technical direction across Core DevOps services, including CI, CD, planning, and source control, while driving architectural convergence, modernization, reliability, and AI-native engineering practices. The role also partners across engineering and product, mentors senior technical leaders, and supports critical technical decisions and incident management.

Responsibilities:

• Set and continuously refine the go forward technical direction for CI, CD, Plan, and source code experiences, aligned against the horizontal architectural initiatives
• Work directly with the VP of Engineering as her technical counterpart on planning, technical investment, and where the group's engineering effort should go
• Translate GitLab's company-wide productivity, quality, and AI native engineering goals into concrete technical direction for Core DevOps, and turn into iterable roadmaps, partnering broadly across the org
• Define what good means in measurable terms for these services, including availability, latency at p95 and p99, pipeline success rate, test reliability, data correctness, and defect escape rate, then hold designs and implementations to it
• Maintain a clear and current picture of systemic technical risk across the group, including single points of failure, unowned critical paths, brittle coupling between CI/CD and Plan, scaling limits, and past decisions that now constrain the roadmap. Drive a prioritized plan to retire it
• Lead the hardest design decisions hands on, writing code, prototypes, and proofs of concept where a design argument needs evidence behind it
• Drive convergence on shared patterns, libraries, and paved paths, reducing how many different ways the same problem gets solved across the group
• Design migration paths that let large, long lived systems change underneath users without breaking them, using incremental cutover, dual run, measurable rollback, and deprecation with clear timelines
• Adopt the platform capabilities coming from GitLab's AI organization and the company's productivity initiatives into Core DevOps, feed this group's requirements back into them, and help prove what works on systems of this scale and maturity
• Serve as the escalation point for complex or contested technical decisions across the group, including those where no single team owns the outcome
• Review significant designs and merge requests in the group's critical paths, and use review to teach rather than only to gate
• Ensure designs hold across GitLab.com, GitLab Dedicated, and Self-Managed deployments, and respect multi-tenant, compliance, and data governance boundaries in each
• Partner with Infrastructure, Security, and SRE so Core DevOps services are observable and debuggable, and so failure modes degrade gracefully instead of cascading
• Make architectural constraints and opportunities clear to Product in roadmap terms, so that technical investment and product ambition get planned together instead of traded off late
• Write clear, opinionated design documents, architecture narratives, and decision records that let teams across the group make aligned decisions independently
• Grow Principal and Staff Engineers across Core DevOps, raise the bar on design rigor and technical writing, and contribute to the technical hiring bar for senior individual contributors
• Participate in the Incident Management on-call rotation to help meet availability goals for GitLab.com, and complete Interview Training to participate in hiring as a technical interviewer or panel member

Requirements:

• 10+ years of software engineering experience, including 4+ years in a Staff, Principal, or equivalent senior technical leadership role
• Deep expertise in AI and ML systems, including large language models, agentic frameworks, and autonomous workflow design at production scale
• Proven track record of leading hands-on technical experimentation, including defining evaluation frameworks, running benchmarks, and translating findings into scalable architecture decisions
• Strong background in scalable, multi-tenant distributed systems, including service decomposition, fault tolerance, observability, and operational resilience
• Experience designing and implementing human-in-the-loop controls, safety guardrails, and responsible AI practices for production systems
• Experience mentoring senior engineers and influencing technical direction across multiple teams or divisions without direct authority
• Ability to work effectively in a fully remote, globally distributed organization with excellent written and asynchronous communication skills