Product Manager (leadership)

Meta Meta · Big Tech · Singapore

Meta is seeking an entrepreneurial Product Management Leader to drive AI transformation across their consumer products. This role involves setting vision and strategy, leading cross-functional teams, and executing AI-native product initiatives. The leader will critically evaluate AI solutions, translate AI capabilities into product visions, champion AI strategies including evals and data strategies, and scale AI best practices across the organization. Responsibilities include defining product requirements, orchestrating complex execution, using AI-enabled tools to build products, and designing sophisticated experiments and evaluations for AI-powered experiences.

What you'd actually do

  1. Is the primary driver for identifying and shaping transformative, long-term opportunities across multiple large Product areas or portfolios, setting vision and strategy that influences Meta’s broader organizational and industry direction.
  2. Drive product development with teams of engineers and designers, while maintaining team health.
  3. Plan, initiate, and manage information technology projects for web-based products, applications, and platforms.
  4. Use AI-enabled tools to build products—setting the standard for PM technical capability.
  5. Define and analyze metrics that inform the success of products.

Skills

Required

  • 12+ years of experience in Product Management and/or Product Design
  • 12+ years of experience working collaboratively with engineering, design and user research teams
  • Critical thinking/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 senior executive audiences
  • BA/BS in Computer Science or related field
  • Experience in a consumer focused technology company
  • Experience building 0-1 AI-native products, platform/ecosystem products, or marketplaces
  • Track record of scaling AI best practices across organizations
  • Track record of successfully executing strategy in APAC

What the JD emphasized

  • Critically evaluate when AI is (and isn't) the optimal solution at portfolio level
  • Champion AI-native strategies including comprehensive evals and data strategies
  • Scale AI best practices (including responsible AI use), workflows, and artifacts across the organization
  • Orchestrate complex execution across multiple organizations by combining AI automation with strategic human oversight at scale.
  • Use AI-enabled tools to build products—setting the standard for PM technical capability.
  • Define and run evaluations (evals) to interpret model outputs at scale—establishing evaluation as a strategic capability for AI-powered experiences.

Other signals

  • AI transformation
  • AI-native strategies
  • AI best practices
  • AI-enabled tools
  • AI-powered experiences