Distinguished Engineer, Agentic SDLC – Non-Linear Productivity

This is a fully remote position, open to applicants in United States, +3 more countries.

📋 Description

• Establish and continuously enhance a comprehensive technical vision for an autonomous, agentic Software Development Life Cycle (SDLC) that aligns with GitLab's product strategy and Engineering job framework.

• Identify and prioritize opportunities for non-linear productivity enhancements throughout the SDLC, aiming for significant 10x improvements.

• Convert ambiguous problem domains into clear, actionable roadmaps in collaboration with Product, AI and ML, and Architecture teams.

• Spearhead hands-on experiments and prototypes focused on autonomous Merge Request (MR) authoring, test generation and triage, security remediation, release readiness, and incident management.

• Design and implement reference architectures that include orchestration patterns, safety guardrails, observability measures, and human-in-the-loop controls.

• Establish evaluation frameworks utilizing offline benchmarks and online experiments.

• Take ownership of high-impact internal use cases from initial concept to adoption and measurable productivity improvements.

• Integrate agentic workflows into everyday engineering practices.

• Define and monitor productivity metrics such as cycle time, Mean Time to Recovery (MTTR), and Merge Request throughput.

• Codify reusable patterns, libraries, and playbooks.

• Transform established internal patterns into safe and reliable product functionalities.

• Ensure adherence to compliance, data governance, and multi-tenant requirements.

• Act as a point of escalation for intricate technical and architectural decisions.

• Mentor Principal and Staff Engineers.

• Draft design documents, architecture narratives, and decision records.

• Represent GitLab at conferences, standards organizations, and within open source communities.

• Collaborate with Security, Compliance, Reliability, and Site Reliability Engineering (SRE) teams on guardrails, monitoring, observability, and resilience strategies.

⛳️ Requirements

• Over 10 years of software engineering experience, including a minimum of 4 years in a Staff, Principal, or comparable senior technical leadership position.

• Extensive knowledge of AI and ML systems, encompassing large language models, agentic frameworks, and autonomous workflow design at a production scale.

• Proven experience in leading hands-on technical experimentation, which includes defining evaluation frameworks, conducting benchmarks, and translating results into scalable architectural decisions.

• Strong foundation in scalable, multi-tenant distributed systems, focusing on service decomposition, fault tolerance, observability, and operational resilience.

• Experience in designing and implementing human-in-the-loop controls, safety guardrails, and responsible AI practices for production systems.

• Demonstrated capability to drive cross-functional alignment among Engineering, Product, Infrastructure, and Data and ML teams on complex and ambiguous technical challenges.

• Experience mentoring senior engineers and influencing technical direction across multiple teams or divisions without direct authority.

• Proficiency in working effectively within a fully remote, globally distributed organization, with excellent written and asynchronous communication skills.

• Familiarity with GitLab's DevSecOps platform, CI/CD primitives, and the software development lifecycle is a significant advantage.

🏝️ Benefits

• A comprehensive benefits package to support your health, finances, and overall well-being.

• Flexible Paid Time Off.

• Access to Team Member Resource Groups.

• Equity Compensation & Employee Stock Purchase Plan.

• Growth and Development Fund.

• Parental Leave.