About GitLab
GitLab is the intelligent orchestration platform for DevSecOps. It 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 over 50% of the Fortune 100 trust GitLab to ship better, more secure software faster. The company embraces AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact.
About the Role
As the Lead Product Marketing Manager, AI at GitLab, you will be instrumental in shaping the market narrative for GitLab's AI capabilities across the software development lifecycle. This role focuses specifically on the GitLab Duo Agent Platform and related AI offerings, helping customers understand how GitLab supports software teams and their AI agents within a unified platform. Sitting at the intersection of product, market insight, and revenue strategy, you will have significant autonomy while collaborating closely with Product Management, Engineering, Sales, Customer Success, and Marketing. You are expected to bring firsthand experience using AI agents in your own marketing workflows, actively building with them to generate insights, pressure-test positioning, and accelerate your work.
What you'll do
- Collaborate on an end-to-end Go-to-Market (GTM) strategy and execution for GitLab Duo Agent Platform and AI capabilities, emphasizing intelligent orchestration for software teams and AI agents across the software lifecycle.
- Lead positioning and narrative for GitLab's AI capabilities, articulating how the platform unifies DevOps, Security, and AI workflows and addresses the "AI Paradox".
- Develop and execute GTM strategies for usage-based AI monetization and consumption-based offerings.
- Partner with Product Management, Sales, Customer Success, and Engineering to understand customer AI modernization journeys, validate market problems, and translate them into clear messaging, revenue plays, pricing strategies, and launch priorities.
- Build and continuously refine compelling positioning and messaging for AI capabilities, including persona-specific content for platform engineering leaders, DevOps directors, technology executives, and developer teams.
- Define and execute comprehensive GTM plans for new AI capabilities, agents, workflows, and usage-based offerings, ensuring timely, impactful launches aligned with sales, field marketing, partner ecosystem, and digital marketing motions.
- Serve as the subject matter expert for AI and intelligent orchestration within Product Marketing, synthesizing analyst feedback, market trends, competitive insights, and customer proof points into differentiated narratives.
- Create and maintain high-impact sales enablement materials (pitches, playbooks, FAQs, objection-handling guides, use case libraries, pricing/packaging comparison guides) to scale AI-focused sales motions.
- Build distinctive external thought leadership grounded in your own practice of using AI agents, sharing original insights from hands-on experimentation.
- Partner with other Product Marketing Managers on AI positioning, usage-based monetization, and GTM strategies.
- Lead complex, cross-functional initiatives involving sales, product, growth, and marketing teams to drive AI adoption and revenue.
What you'll bring
- Strong product marketing experience owning complex, technical B2B SaaS products from discovery through launch.
- Proven success in usage-based monetization, consumption pricing models, and GTM strategies driving measurable revenue impact in AI or developer tools markets.
- Deep understanding of AI/ML technologies, agentic workflows, LLM orchestration, and the software development lifecycle.
- Practical exposure to capabilities such as AI coding assistants, agentic automation, multi-agent systems, Model Context Protocol (MCP), and intelligent orchestration concepts.
- Demonstrated AI-first working style: active use of AI agents for positioning, research, competitive analysis, and content creation, with specific examples of insights generated or decisions influenced by agent-assisted workflows.
- Experience across multiple domains within DevSecOps.