Distinguished Engineer, Agentic Sdlc & Non‑linear Productivity

GitLab GitLab · Enterprise · Canada +1 · Remote · Architecture Engineering

Distinguished Engineer role focused on pioneering and scaling autonomous, agentic SDLC capabilities within GitLab. The role involves identifying productivity opportunities, leading hands-on experiments with AI agents for tasks like MR authoring and security remediation, designing reference architectures with guardrails and observability, defining evaluation frameworks, and converting proven internal patterns into customer-facing product capabilities. Requires deep expertise in AI/ML systems, agentic frameworks, and production-scale autonomous workflows.

What you'd actually do

  1. Define and continuously refine a company-wide technical vision for autonomous, agentic SDLC that aligns with GitLab's product strategy and Engineering job architecture.
  2. 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.
  3. Translate ambiguous problem spaces into concrete, iterable roadmaps in partnership with Product, AI and ML, and Architecture teams.
  4. 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.
  5. Design and implement reference architectures for agentic SDLC inside GitLab, including orchestration patterns, safety guardrails, observability, and human-in-the-loop controls.

Skills

Required

  • 10+ years of software engineering experience
  • 4+ years in a Staff, Principal, or equivalent senior technical leadership role
  • Deep expertise in AI and ML systems
  • Large language models
  • Agentic frameworks
  • Autonomous workflow design at production scale
  • Hands-on technical experimentation
  • Defining evaluation frameworks
  • Running benchmarks
  • Translating findings into scalable architecture decisions
  • Scalable, multi-tenant distributed systems

What the JD emphasized

  • autonomous, agentic SDLC
  • AI agents
  • agentic workflows
  • safety guardrails
  • evaluation frameworks
  • customer-facing product capabilities
  • production scale
  • autonomous MR authoring
  • security remediation
  • incident response

Other signals

  • AI agents
  • autonomous workflows
  • production scale
  • customer-facing AI product