Distinguished Engineer, Agentic SDLC & Non‑Linear Productivity
G
GitLabDevSecOps
Remote, Canada; Remote, Poland; Remote, United Kingdom; Remote, United StatesFull-TimePrincipal
Salary250,000 - 349,000 USD per year
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Job Details
- Experience
- 10+ years of software engineering experience, including 4+ years in a Staff, Principal, or equivalent senior technical leadership role
- Required Skills
- CI/CDLLMDistributed Systems
Requirements
- 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, including large language models and agentic frameworks
- Experience in autonomous workflow design at production scale
- Proven track record of leading technical experimentation and defining evaluation frameworks
- Strong background in scalable, multi-tenant distributed systems
- Experience designing human-in-the-loop controls and responsible AI practices
- Demonstrated ability to drive cross-functional alignment across Engineering, Product, Infrastructure, and Data teams
- Experience mentoring senior engineers and influencing technical direction
- Ability to work effectively in a fully remote, globally distributed organization
- Proficiency in written and asynchronous communication
- Familiarity with GitLab's DevSecOps platform and CI/CD primitives (preferred)
Responsibilities
- 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
- Lead hands-on experiments and prototypes to validate where agentic workflows can fully own or materially reshape engineering tasks
- Design and implement reference architectures for agentic SDLC inside GitLab, including orchestration patterns, safety guardrails, and observability
- Define evaluation frameworks using offline benchmarks and online experiments to measure correctness, latency, safety, and productivity impact
- Work directly with engineering teams to embed agentic workflows into day-to-day development
- Mentor Principal and Staff Engineers working on AI and agentic efforts
- Partner with Security and Compliance to define guardrails and review processes for agentic features
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