Distinguished Engineer, Agentic SDLC & Non‑Linear Productivity

GitLab is looking for a Distinguished Engineer to pioneer and scale autonomous, agentic SDLC capabilities across the company. This is the most senior level of individual technical leadership at GitLab: you will immerse yourself in GitLab's product and internal engineering workflows, identify classes of problems that AI agents can wholly or largely own, validate them through rigorous experimentation, and codify patterns that can be productized for millions of users. You will act as a bridge between Architecture, Product, Infrastructure, and Data and ML teams, proving agentic capabilities internally first and then scaling them reliably and securely to customers. Depending on depth and breadth of experience, the role may be scoped as Distinguished Engineer or Fellow Engineer.

Responsibilities

• Define and continuously refine a company-wide technical vision for autonomous, agentic SDLC aligned with GitLab's product strategy.
• Identify and prioritize non-linear productivity opportunities across the SDLC, from planning and coding to review, security, compliance, and operations, targeting 10x step changes rather than incremental gains.
• Lead hands-on experiments and prototypes to validate where agentic workflows can fully own engineering tasks, including autonomous MR authoring, test creation and triage, security remediation, release readiness, and incident response.
• Design reference architectures for agentic SDLC inside GitLab, covering orchestration patterns, safety guardrails, observability, and human-in-the-loop controls.
• Define evaluation frameworks using offline benchmarks and online experiments to measure correctness, latency, safety, cost, and productivity impact.
• Own a small set of high-impact internal use cases as pathfinders, driving them from concept through adoption to measurable productivity gains, tracked via cycle time, MTTR, and MR throughput.
• Work with Product Management and Engineering leadership to convert proven internal patterns into product capabilities, respecting multi-tenant, compliance, and data governance requirements.
• Mentor Principal and Staff Engineers on AI and agentic efforts, write opinionated design documents and decision records, and represent GitLab in conferences and open source communities.

Qualifications

• 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 hands-on technical experimentation: 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 human-in-the-loop controls, safety guardrails, and responsible AI practices for production systems.
• Demonstrated ability to drive cross-functional alignment across Engineering, Product, Infrastructure, and Data organizations.