Worth applyingGitLab

AI Transformation Owner, Product & Design

Skills and tasks

Suggested skills

  • Model Context Protocol (MCP) integration
  • LLM evaluation and benchmark design
  • Internal community and champion program design

Skill-to-task connections are not available yet.

Tasks from the posting

  • Align functional AI strategy

    Your edge

  • Map end-to-end workflows

    You + AI

  • Manage AI request intake

    Your edge

  • Build Champion peer network

    Your edge

  • Build low-code AI agents

    You + AI

  • Author agent skills files

    You + AI

  • Configure MCP servers

    You + AI

  • Run agent performance evaluations

    You + AI

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More analysis and source details
31%
of this job is already automatable.
69% is classified as human or shared work.
0 AI does it5 You + AI3 Your edgeof 8 duties

Your edge · 3 things

  • Securing managerial consent from peer leads to dedicate five to ten percent of staff time to Champion duties.
  • Evaluating whether an operational bottleneck requires an architectural workflow overhaul rather than simple automation.
  • Saying no to low-impact AI proposals from senior internal stakeholders to protect engineering bandwidth.
The fieldgrowing · 10+ years

Enterprises are committing substantial capital budgets to internal operational AI deployment, shifting headcount into internal transformation and enablement. While the specific title may evolve, the demand for operators who translate business bottlenecks into automated agent architectures continues to expand across tech orgs.

Do this week

  1. Model Context Protocol (MCP) integrationDirectly required to connect company systems to autonomous agents securely.
  2. LLM evaluation and benchmark designAllows rigorous tracking of agent quality drift after platform updates.
  3. GleanBuild AI agents using no-code and low-code platforms (e.g. Glean, Workato, similar tools).

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