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Details
Developing and launching go-to-market strategies for GitLab Duo Agent Platform and AI offerings.
Using AI agents to accelerate competitive analysis, synthesize customer feedback patterns, and generate first-draft positioning hypotheses — then sharing those methods as part of GitLab's thought leadership
Creating persona-based messaging for organizations moving from individual AI coding tools to team and agent collaboration across the software lifecycle.
Building thought leadership around intelligent orchestration, unified workflows, and how teams stay in flow with AI agents.
Supporting launches for new AI capabilities, agentic workflows, and related monetization approaches.
What you'll do
Collaborate on an end-to-end GTM strategy and execution for GitLab Duo Agent Platform and AI capabilities, emphasizing how intelligent orchestration enables software teams and their AI agents to stay in flow across the complete software lifecycle—addressing the "AI Paradox" where faster coding doesn't translate to faster delivery when the rest of the lifecycle remains fragmented.
Lead positioning and narrative for GitLab's AI capabilities, articulating how we bring software teams and their AI agents together, eliminate gaps between traditionally-manual software lifecycle stages, and unify DevOps, Security, and AI workflows into a single orchestrated system where teams orchestrate from above while agents execute within. Your ability to articulate this vision will be strengthened by your own experience working alongside agents and understanding their capabilities and limitations firsthand.
Develop and execute go-to-market strategies for usage-based AI monetization and consumption-based offerings that demonstrate clear customer value.
Partner with Product Management, Sales, Customer Success, and Engineering to understand how customers are navigating AI modernization journeys, validate market problems around toolchain fragmentation and tool-specific AI agents, 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 go-to-market plans for new AI capabilities, agents, workflows, and usage-based offerings, ensuring launches are timely, impactful, and tightly aligned with sales, field marketing, partner ecosystem, and digital marketing motions while delivering measurable pipeline and revenue impact.
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 that position GitLab's architectural advantages over AI coding tools and fragmented toolchain approaches.
Create and maintain high-impact sales enablement materials such as pitches, playbooks, FAQs, objection-handling guides, use case libraries, and pricing and packaging comparison guides that help scale AI-focused sales motions and accelerate deal velocity.
Build distinctive external thought leadership grounded in your own practice of using AI agents — sharing original insights from hands-on experimentation. You'll speak, write, and brief from a practitioner's perspective that gives GitLab's voice authenticity and specificity in a market full of abstract AI narratives.
Partner with Product Marketing Managers on AI positioning, usage-based monetization, and go-to-market strategies within your area of expertise.
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, with proven success in usage-based monetization, consumption pricing models, and go-to-market strategies that drive measurable revenue impact in AI or developer tools markets.
Deep understanding of AI/ML technologies, agentic workflows, LLM orchestration, and the software development lifecycle, with 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: you already use AI agents as core to how you develop positioning, conduct research, analyze competitors, and create content. You should be able to walk us through specific examples of insights you've generated or decisions you've made differently because of your agent-assisted workflow.
Experience across multiple domains within DevSecOps, enabling you to position AI capabilities across the complete software lifecycle from planning through deployment and operations.
Proven experience positioning platform solutions with ability to articulate architectural advantages of unified platforms with complete context over fragmented toolchains with tool-specific AI agents.
Strong understanding of key personas including platform engineering leaders, DevOps directors, AI/ML leaders, and developers, and how they evaluate, purchase, and adopt AI solutions across different organizational AI maturity levels (evaluating AI, using AI coding tools, AI-first organizations).
How GitLab Supports Full-Time Employees
Benefits to support your health, finances, and well-being
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Experience working with large B2B enterprise customers navigating AI transformation, translating their challenges with fragmented trust, context, regulations, and budgets into clear positioning, differentiated messaging, and scalable go-to-market strategies.
Track record of successfully launching new products, usage-based pricing models, or consumption-based offerings, including defining monetization strategy, coordinating partner ecosystem activities, and measuring business impact through pipeline generation, usage metrics, and revenue growth.
Ability to synthesize qualitative feedback, product usage data, win/loss analysis, and market research into clear, actionable messaging frameworks, pricing recommendations, consumption model optimization, and revenue plays that address both technical and business buyer needs.
Strong written and verbal communication skills, with ability to explain complex AI concepts (agentic workflows, unified data models, intelligent orchestration, MCP integration) to both technical and non-technical audiences through presentations, content, and enablement materials.
Familiarity with AI coding tools landscape and ability to position GitLab's team-level orchestration across the complete software lifecycle.
Strategic thinking about market opportunities in AI for software teams, competitive positioning against both AI coding tools and DevOps platforms, and business model innovation around usage-based pricing that demonstrates clear customer value.
Proven experience being self-directed and working with minimal supervision, able to coordinate across many teams and lead cross-functional initiatives.
Data-driven approach, using data to measure results, inform decision-making, and develop strategy.
Openness to learning, with transferable skills from related areas such as MLOps, platform engineering, or developer experience, and a self-directed approach to staying current on AI industry trends, agentic AI developments, and enterprise AI adoption patterns.