Distinguished Engineer, Agentic SDLC & Non‑Linear Productivity

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the Role We are looking for a Distinguished Engineer to pioneer and scale autonomous, agentic SDLC capabilities across GitLab. Distinguished Engineers are recognized experts across multiple technology domains and represent the most senior level of technical leadership within and across divisions at the company. In this role you will deeply immerse in GitLab's product and internal engineering workflows to identify classes of problems that can be wholly or largely addressed by AI agents, validate them through rigorous experimentation in production-adjacent environments, and codify patterns that can be productized for our millions of users. You will act as a bridge between Architecture, Product, Infrastructure, and Data and ML teams, ensuring that agentic capabilities deliver durable value internally first and then scale reliably and securely to our customers. This role reports to a Director-level engineering leader. What You'll Do Define and continuously refine a company-wide technical vision for autonomous, agentic SDLC that aligns with GitLab's product strategy and Engineering job architecture. 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. Translate ambiguous problem spaces into concrete, iterable roadmaps in partnership with Product, AI and ML, and Architecture teams. Lead hands-on experiments and prototypes to validate where agentic workflows can fully own or materially reshape engineering tasks, including autonomous MR authoring, test creation and triage, security remediation, release readiness, and incident response. Design and implement reference architectures for agentic SDLC inside GitLab, including 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 of agentic workflows. Select and own a small set of high-impact internal use cases as pathfinders and drive them from concept through adoption to measurable productivity gains. Work directly with engineering teams to embed agentic workflows into day-to-day development, ensuring they are trusted, observable, and resilient. Define and track core productivity metrics such as cycle time, MTTR, and MR throughput, and link agentic interventions to real business outcomes. Capture and codify reusable patterns, libraries, and playbooks that other teams can adopt with minimal friction. Work with Produc