Lead, Learning Architecture & AI Enablement

GitLab GitLab · Enterprise · Canada +1 · Talent Management & Development

Lead the strategy and systems for GitLab's global learning ecosystem, focusing on designing AI-powered learning experiences and leading an enterprise AI fluency program. This role involves architecting an AI-native learning ecosystem with adaptive paths, coaching agents, and automated workflows, and partnering with various teams to integrate AI capabilities into enterprise platforms.

What you'd actually do

  1. Architect GitLab's AI-native learning ecosystem, including adaptive learning paths, coaching agents, bots, intelligent recommendations, and automated content workflows.
  2. Lead GitLab's company-wide AI fluency and enablement strategy in partnership with the Enterprise AI team, from baseline literacy through builder capability.
  3. Embed AI fluency into onboarding, leadership development, and role-specific learning pathways.
  4. Own the multi-year learning platform strategy and roadmap, including platform evaluations, migrations, integrations, and capability expansions.
  5. Drive operational excellence across the Talent Management & Development team by managing the product roadmap, release schedule, intake processes, documentation, automations, and cross-functional coordination.

Skills

Required

  • Experience leading enterprise-scale AI enablement or AI fluency programs at technology companies, with evidence of workforce adoption and capability growth.
  • Hands-on experience designing and deploying AI agents, building intelligent workflows, working with large language model application programming interfaces, and integrating AI capabilities into enterprise platforms.
  • Experience designing learning ecosystems that use AI for adaptive learning, intelligent recommendations, coaching, or automated content workflows.
  • Experience building and owning multi-year technology and program roadmaps, communicating tradeoffs, and making investment decisions based on outcomes.
  • Deep knowledge of learning technology ecosystems, including learning management system administration, platform evaluations, migrations, integrations, and vendor management.
  • Ability to translate talent and learner needs into clear technical requirements and work with engineers on application programming interfaces, data structures, and integration patterns.
  • Strong program management skills, including roadmaps, intake, release schedules, triage, documentation, and automation.
  • Experience with instructional design, adult learning principles, analytics, executive communication, and global compliance training.

What the JD emphasized

  • AI fluency
  • AI agents
  • intelligent workflows
  • AI-native platform design
  • AI fluency into onboarding
  • AI fluency into leadership development
  • AI fluency into role-specific learning pathways
  • AI adoption

Other signals

  • AI-native learning ecosystem
  • AI fluency program
  • AI agents and intelligent workflows