AI-Native Product Manager: Scale & Impact

Meta

San Francisco (CA)

On-site

USD 173,000 - 241,000

Full time

14 hours ago
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Job summary

Meta is seeking Product Managers who value moving quickly and want to lead AI-native product development at scale. You will work with cross-functional teams including engineers, designers, data scientists and researchers to define strategy, build roadmaps, and measure success.

Demonstrated experience in managing products through the full lifecycle and scaling AI-enabled strategies is essential. You will mentor others, drive complex execution across multiple workstreams, and advocate for

Qualifications

  • 8+ years of industry experience with at least 3 years in Product Management.
  • Experience managing a product through the full product lifecycle.
  • Experience developing and scaling AI-native strategies including evals and data strategies across teams.
  • Extensive understanding of analyzing large-scale data sets and making data-driven decisions.
  • Experience leading cross-functional product teams across a full product line.

Responsibilities

  • Lead a complex product area and define success.
  • Develop a roadmap and drive progress against goals and milestones.
  • Collaborate with engineers, designers, data scientists, and researchers to translate AI capabilities into product value.
  • Scale AI best practices and responsible AI use across product teams.

Skills

AI-enabled tools
Cross‑functional leadership
Data-driven decisions

Education

Bachelor's degree or equivalent (STEM preferred)

Tools

AI platforms

Job description

Meta is seeking Product Managers who value moving quickly and want to lead AI-native product development at scale. You will work with cross-functional teams including engineers, designers, data scientists and researchers to define strategy, build roadmaps, and measure success.

Demonstrated experience in managing products through the full lifecycle and scaling AI-enabled strategies is essential. You will mentor others, drive complex execution across multiple workstreams, and advocate for

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