Product Manager, Identity

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists and researchers to build products.

We are looking for Product Managers who value moving quickly and lead AI-native product development at scale.

• 8+ years of relevant industry experience with at least 3 years in Product ManagementBachelor's degree (or relevant degree equivalent): STEM subject ideal but not essential (Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences)
• Experience leading cross-functional product team(s) across a full product line: Crafting product mission and strategy, defining product requirements, coordinating resources from other groups (marketing, legal, etc.), and driving the team to achieve key milestones and goals
• Experience managing a product through the full product lifecycle
• Proven experience to drive a step change in the performance of a product and the effectiveness of the team that delivers that product
• Extensive understanding in analyzing large-scale, complex data sets and making effective decisions based on data
• Demonstrated proficiency using AI-enabled tools to build product artifacts
• Experience developing and scaling AI-native strategies including evals and data strategies across teams
• Experience integrating a diverse set of requirements from a broad set of users as well as context into a single coherent product strategy
• Experience leading and motivating teams and influencing across an organisation
• Demonstrated experience in communication, bringing extreme clarity to complex and technical messages across all audience levels
• Experience identifying and hiring the right talent to build an AI-capable cross-functional team
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)