AI Transformation Owner, Product & Design
Job description
An AI Transformation Owner at GitLab shapes a function's AI strategy and builds no-code/low-code AI solutions to deliver it, working in partnership with an AI Engineer from the Enterprise AI team. The role combines product management, process mapping, change management and hands-on agent building.
At a glance
- Employment
- Full-time · Employee (employment agreement)
- Work mode
- Remote · United States
- Pay
- USD 203,200 – 345,600 / year
What you'll do
- Own your function's AI strategy, aligned with your Executive Sponsor and business priorities; understand which metrics matter, identify what will move the needle, define how you'll measure impact, and track progress over time
- Map how work flows across your function end-to-end, including handoffs upstream and downstream to other orgs; identify where the real constraints are and focus on 100x problems
- Manage intake of AI requests, ideas, and pain points from across the function, including via your Champion network
- Prioritize strategically against business outcomes and executive guidance; hold the line on priorities and ensure the AI Engineer's time is spent on the highest-impact work
- Reimagine, not just automate: challenge your org to think beyond injecting AI into existing workflows and work with Enterprise AI to spot opportunities to fundamentally rethink how work gets done
- Drive adoption and change management together with the AI Engineer; create channels, rituals, and feedback loops that make AI visible in your function, including shared spaces, office hours, onboarding for new hires, and celebration of wins
- Coordinate with Enterprise AI to ensure your function benefits from patterns, tools, and learnings emerging across other parts of the business
- Build and bridge the Champion network in your function: identify and recruit Champions across sub-teams (5-10% time, formally agreed with their manager), run a regular Champion sync, host demos, and act as their bridge to Enterprise AI
- Build AI agents using no-code and low-code platforms (e.g. Glean, Workato, similar tools), going from idea to working prototype without waiting for engineering
- Author and iterate on skills files that define how AI agents behave; refine instructions based on real usage and share reusable skills across the function
- Configure MCP servers and tools, giving agents access to the business systems they need; partner with the AI Engineer on what to connect and how to do it securely
- Own your function's fleet of agents, tracking KPIs, running evaluations after model or data changes, and iterating based on what you learn
- Expect to rebuild: be comfortable sunsetting your own work when a better approach emerges and help your org stay current
What we're looking for
- Deep knowledge of your function's operations: understand how work moves through your org, where it gets stuck, and why; trace a process end-to-end and explain how it connects to the teams around it
- Strategic prioritization skills: have managed competing demands and can make hard calls about what matters most, thinking in terms of business outcomes, not activity
- A product management mindset: naturally think about intake, backlog, iteration, and adoption; comfortable defining success metrics and holding yourself accountable to them
- Strong communication and influence: credibility and interpersonal skills to say "not yet" to some teams and "think bigger" to others
- Cross-functional instincts: default to understanding how your org's processes affect and are affected by the teams around you
- Experience building peer networks or communities of practice: have recruited and sustained volunteer contributors before, whether as a guild lead, champion program owner, or community organizer
- Comfortable building with AI tools: able to build a working agent, configure a skill, connect an MCP server, and troubleshoot when something isn't working (power user, not software engineer)
- Ready to learn fast: experience with or willingness to quickly pick up no-code/low-code AI platforms, prompt engineering, and agent configuration
- Strong conceptual understanding of AI capabilities - summarization, classification, generation, automation, agentic workflows - and a commitment to staying current
- Ability to map data flows - structured and unstructured; understand where agents need context and where humans should interface with automated workflows and at what steps
Your team
Enterprise Technology & AI organization (partnering with Enterprise AI)
You will partner closely with Enterprise AI within the Enterprise Technology & AI organization, while remaining embedded in your own function. Enterprise AI provides the technical delivery capability, platforms, and patterns; you provide the business context, prioritization, building at the no-code layer, and adoption muscle.
Apply
Direct apply at GitLab
Opens the job posting at GitLab
About GitLab
The intelligent orchestration platform for DevSecOps
GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100 trust GitLab to ship better, more secure software faster.
Key facts
- DevSecOps software
- More than 50 million registered users
- More than 50% of the Fortune 100 trust GitLab
- All roles are remote, however some roles may carry specific location-based eligibility requirements
- GitLab hires new team members in countries around the world