Drimva

Meta

Lead, Product Content Engineering

$242K–$296K

Menlo Park, CA +2 · Full-time · Posted Jun 26, 2026

Location
Menlo Park, CA
New York, NY
San Francisco, CA
Experience
10+ years in content quality and relevance; 3+ years managing and developing individual contributors; 1+ year working with GenAI; 2+ years working closely with ranking teams; 4+ years in product management, data analytics, or content operations in a large-scale content platform.
Education
BA or BS in Computer Science, Data Science, Linguistics, or related field.

About the job

Leads a team developing content strategies and systems to evaluate and improve AI-powered experiences across Meta’s products.

What you'll do

  • Develop strategies for evaluating LLMs at scale and build automated evaluation tooling.
  • Lead, hire, mentor, and develop a team of content engineers.
  • Drive cross-functional work with engineering, data science, and product teams to align AI behaviors and content experiences with user expectations.

What they ask for

  • 10+ years improving content quality and relevance on content platforms, including work with video creators, ranking systems, and content strategy.
  • 3+ years hiring, managing, and developing individual contributors; 2+ years working closely with ranking teams.
  • 1+ year working with GenAI products, prompt engineering, annotation, and/or content evaluation and analysis.
  • BA or BS in Computer Science, Data Science, Linguistics, or a related field.

Nice to have

  • Experience with data visualization tools such as Tableau.
  • Demonstrated ongoing AI skill development, such as prompt/context engineering or agent orchestration.

Pay

$242,000/year to $296,000/year base salary

Tools

LLMs, GenAI, Tableau

AI focus

Evaluates LLMs at scale, builds automated evaluation tooling, and aligns AI behaviors and content experiences with user expectations; the role also involves responsible AI practices and integrating AI tools into workflows.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)