Meta Product Managers

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. This role will own our company’s approach to finding and removing bad actors running scam ads on Meta’s advertising platform. Scams are one of the most important problems we face as a company, with incredibly sophisticated adversaries. Finding and removing these bad actors whilst protecting benign businesses requires a deep understanding of how scams manifest on our platform and how we can make it financially unviable for them to continue. Success will require a deep understanding of integrity, the ability to influence teams across multiple orgs, define the most effective strategy to fight online scams, and being able to quickly jump between being deep in the detail to articulating the overall progress we’re making on ad scams to senior leadership.

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.