Engineering Manager, AI Governance at GitLab

Lead the AI Governance engineering team and support its growth as the product and roadmap expand, building a high-performing organization that delivers roadmap commitments on schedule.
Own delivery planning and execution across the AI Governance roadmap, including audit events, registry and policy controls, and governance reporting, to ship key milestones on schedule and keep roadmap delivery predictable.
Build the team by partnering with Talent Acquisition, running hiring processes, and helping attract backend engineering talent across levels to meet hiring goals tied to roadmap needs.
Partner with Product, Design, and peer engineering leaders to prioritize work, plan capacity, and maintain clear alignment on scope and sequencing to reduce delivery delays and tradeoffs.
Collaborate with the Duo Agent Platform team and other adjacent teams to deliver systems that work reliably across product boundaries and reduce integration issues in production.
Develop engineers through regular 1:1s, performance feedback, and career development conversations in an all-remote environment to support team growth and improve retention.
Drive engineering quality through strong testing practices, sound architecture, and a delivery cadence that builds customer trust and reduces production defects.
Represent the team in stage planning and section-level leadership reviews, providing clear updates on progress, risks, and tradeoffs to support timely decisions and keep roadmap execution on track.

Experience leading backend product engineering teams in areas such as security, compliance, observability, or AI-related systems.
Technical knowledge of audit systems, event streaming, policy enforcement, or compliance tooling, with the ability to guide architectural decisions.
Track record of hiring, developing, and supporting engineers across different levels and helping teams grow sustainably.
Comfort working in an asynchronous, documentation-focused organization with collaborators across multiple time zones.
Ability to manage cross-functional work involving Product, Design, Legal, and adjacent engineering teams.
Familiarity with compliance, audit, or governance products, especially in environments serving regulated organizations.
Understanding of AI agent infrastructure, large language model orchestration, or Model Context Protocol tooling, with the ability to apply that knowledge to technical direction and team planning.
Ability to recognize transferable experience and evaluate candidates based on relevant skills across enterprise software, distributed systems, or regulated product environments.

Engineering Manager, AI Governance