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

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

Preferred Qualifications
• 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
• 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