Engineering Manager, AI Engineering: Chat

GitLab GitLab · Enterprise · AMERICAS +1 · Remote · AI Engineering

Engineering Manager for the GitLab Duo Chat team, responsible for managing a team of engineers building AI-powered product experiences across the DevSecOps lifecycle. The role involves technical architecture, execution, and improving quality, testing, and performance for AI agents at scale.

What you'd actually do

  1. Manage a team of experienced frontend, backend, and AI engineers to deliver GitLab Duo Chat roadmap commitments across the DevSecOps lifecycle.
  2. Partner with product and UX teams to define requirements and deliver AI features that address customer needs and improve answer quality.
  3. Participate in technical architecture and development work for systems that run AI agents at scale, with a focus on reliability, performance, and maintainability.
  4. Guide day-to-day execution by setting clear direction, tracking progress against milestones, and removing blockers to keep delivery on schedule.
  5. Coach engineers through feedback, guidance, and development conversations that foster each engineer's growth and overall team performance.

Skills

Required

  • Experience managing engineering teams in a distributed environment
  • Strong software engineering foundation
  • Hands-on familiarity with agentic AI or generative AI applied to software development workflows
  • Ability to work effectively through ambiguity, changing requirements, and fast-moving product development
  • Clear communication and collaboration skills
  • Dedication to coaching engineers and creating an inclusive, constructive team environment
  • Comfort balancing people management with technical involvement

Nice to have

  • Openness to transferable experience from different technical backgrounds if it aligns with managing AI-powered product teams.

What the JD emphasized

  • AI agents at scale
  • reliability, performance, and maintainability
  • AI-powered chat workflows reliable in production
  • agentic AI or generative AI applied to software development workflows

Other signals

  • managing a team of engineers building AI-powered product experiences
  • technical architecture and development work for systems that run AI agents at scale
  • improve quality, testing, and performance practices that increase coverage, strengthen observability, and keep AI-powered chat workflows reliable in production