Product Manager

MetaBellevue, WashingtonOn-siteFull-timeMid level, 2–5 yearsListed 11 hours ago

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About this role

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.

Responsibilities

Be responsible for driving one or more projects within a product area. Define success metrics, prioritize product problems and identify the best solutions to achieve the overall goals
Work with the cross-functional team to develop a roadmap, drive progress against milestones and resolve blockers, whilst maintaining team health
Gather and analyze user research, product insights and market analysis to inform product decisions
Coordinate effectively across all functions relevant to your product area, aligning and influencing roadmaps where appropriate
Communicate clearly upwards and sideways on product plans and progress

Qualifications

3+ years product management or related industry experience
Bachelor's degree (or relevant degree equivalent): STEM subject ideal but not essential (Computer Science, Engineering, Information Systems, Analytics, Mathematics, Physics, Applied Sciences)
Experience working with a cross-functional product team on key product projects: Crafting product mission and strategy, defining product requirements, and driving the team to achieve key milestones and goals
Proven experience to have an impact on the product outcomes and improve the effectiveness of a product team
Extensive understanding to analyze data and deploy it to make the right decisions for a product
Experience using a mixture of approaches to understand requirements from users and identifying the appropriate product solution
Experience leading and motivating a product team
Clear and concise communication 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)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies