Principal Product Manager, AI Custom Models

As a Principal Product Manager you will shape a critical part of GitLab's AI product direction by helping customers run advanced AI capabilities in environments that match their infrastructure, security, and deployment needs. The role focuses on custom models and self-hosted AI experiences, where product decisions balance model choice, agent-based workflows, platform usability, and operational realities like configuration, infrastructure, and hardware. In your first year you will bring clarity to the product area, guide execution on high-impact work, and help GitLab build a more flexible AI offering for customers who need self-managed options.

Responsibilities

• Lead product strategy and roadmap definition for custom models and self-hosted AI capabilities within GitLab.
• Drive discovery, prioritization, and delivery for features supporting model flexibility, self-managed deployments, and AI agent orchestration.
• 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 stakeholders across GitLab AI initiatives to ensure this product area fits the broader platform strategy.
• Guide tradeoff decisions with a strong focus on customer value, technical feasibility, and long-term platform quality.
• Communicate plans, decisions, and priorities transparently so distributed teams can execute asynchronously.

Qualifications

• Experience owning product strategy for technical platform, infrastructure, or AI-driven products.
• Knowledge of AI model ecosystems, including custom, open, and 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 configuration, infrastructure, deployment patterns, and hardware-related constraints.
• Experience leading complex product work with multiple stakeholders and making clear decisions amid technical ambiguity.
• Judgment to operate at principal scope, with ownership across strategy, execution, and cross-functional alignment.
• Openness to transferable experience from DevSecOps, developer platforms, infrastructure software, or applied AI products.