Principal Product Manager, AI Custom Models

What you’ll do

• Lead product strategy and roadmap definition for custom models and self-hosted AI capabilities within GitLab.
• Drive discovery, prioritization, and delivery for features that support model flexibility, self-managed deployments, and AI agent orchestration use cases.
• Collaborate closely with engineering, design, and other product leaders to turn complex customer and technical needs into clear product direction.
• Define product requirements that account for infrastructure, configuration, deployment, and hardware considerations in self-hosted environments.
• Partner with internal stakeholders across GitLab AI initiatives to ensure this product area fits into the broader platform strategy.
• Guide tradeoff decisions with a strong focus on customer value, technical feasibility, and long-term platform quality.
• Support knowledge transfer and continuity as the team grows and evolves, helping new work move forward with context and clarity.
• Communicate plans, decisions, and priorities in a transparent way that helps distributed teams execute asynchronously.

What you’ll bring

• Experience owning product strategy for technical platform, infrastructure, or AI-driven products.
• Knowledge of AI model ecosystems, including custom model options, open models, or open weight models, and the product decisions involved in supporting them.
• Familiarity with self-hosted or self-managed software and the operational needs of customers running software in their own environments.
• Ability to work effectively with engineers on topics such as configuration, infrastructure, deployment patterns, and hardware-related constraints.
• Experience leading complex product work with multiple stakeholders and making clear decisions in areas with technical ambiguity.
• Skill in written and verbal communication, with the ability to explain product direction clearly in a distributed, asynchronous environment.
• Judgment to operate at principal scope, with ownership across strategy, execution, and cross-functional alignment.
• Openness to bringing transferable experience from adjacent areas such as DevSecOps, developer platforms, infrastructure software, or applied AI products.