Product Manager, Central Products

Meta•Menlo Park, CA

About The Position

Meta Product Managers work with cross-functional teams of engineers, designers, data scientists, and researchers to build products. We are looking for extremely effective Product Managers to help innovate and execute product initiatives across the company, value moving quickly, and lead AI transformation at scale. This job description represents different full-time roles across Meta.

Requirements

10+ years product management and/or Product Design
10+ years of experience working collaboratively with engineering, design and user research teams
Experience navigating through the full product life-cycle, integrating customer feedback into product requirements, driving prioritization, and pre- and post-launch execution
Critical thinking and analytical leadership experience
Demonstrated proficiency using AI-enabled tools to build product artifacts at scale
Experience developing and championing AI-native strategies across organizations
Experience presenting to executive audiences
BA/BS in Computer Science or related field

Nice To Haves

Experience building 0-1 AI-native products, platform/ecosystem products, or marketplaces
Experience in a consumer-focused technology company
Track record of scaling AI best practices across organizations

Responsibilities

Is the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals
Generate buy-in and drive consensus across organizations. Bring clarity and structure to ambiguous opportunities. Consistently demonstrate initiative and execute with limited oversight
Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis
Translate AI capabilities into compelling, differentiated product visions that define market categories
Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement
Drive product development with teams of engineers and designers, while maintaining team health
Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones
Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale
Foster a culture of rapid experimentation and learning that becomes a competitive advantage
Scale AI best practices (including responsible AI use), workflows, and artifacts across the organization so capability compounds exponentially
Plan, initiate, and manage information technology projects for web-based products, applications, and platforms
Orchestrate complex execution across multiple organizations by combining AI automation with strategic human oversight at scale
Maximize efficiency in a constantly evolving environment where the process is fluid and creative solutions are the norm
Use AI-enabled tools to build products—setting the standard for PM technical capability
Interpret research and state-of-the-art learnings to design product strategy and apply rigorous logical reasoning at the frontier
Demonstrate expert understanding of system/architecture trade-offs and how they impact user experience and business outcomes
lead strategic technical decisions with engineering leadership
Integrate data, usability studies, research, and market analysis into product strategies and requirements to enhance user satisfaction and improve engineer productivity
Express complex and technical concepts at the right altitude, choosing the right medium and level of detail for the audience (XFN partners, execs, engineering, etc.)
Understand Meta's strategic and competitive position and deliver products that are aligned with our mission and recognized best in the industry
Define and analyze metrics that inform the success of products. Identify and track key performance metrics. Drive decision-making through user insights, quantitative analysis, and AB testing
Design sophisticated experiments and interpret results (leveraging AI) to drive strategic product decisions
Define and run evaluations (evals) to interpret model outputs at scale—establishing evaluation as a strategic capability for AI-powered experiences