Product Operations Manager, Model Quality

Meta is seeking a Product Operations Manager to join our Product Operations Foundations team and drive model quality across all Meta surfaces. We are in the middle of a transformation, becoming an AI-driven, IC-led organization that scales through orchestration, deep product expertise, and technical excellence. Our team is building and operating autonomous agents that handle end-to-end workflows (triage, bug resolution, launches, dogfooding, evals) with minimal human intervention.

If you're energized by owning complex quality programs end-to-end, building and operating AI-driven workflows, and driving measurable product improvements in a fast-paced environment, this role is for you.

You will be responsible for managing and evaluating our AI solutions and infrastructure to improve precision, prevent drift, and maintain real-time observability. This role is expected to set strategy for LLM models, determine areas of investment for increasing accuracy, advise leadership on impending risks, define roadmaps and reporting strategy to shape the future of our AI work. As part of this work, you will be expected to build and maintain industry-wide expertise, develop effective cross-functional relationships, advise engineering and cross-functional partners on areas of investment, determine staffing needs, and solution against critical bottlenecks.

Bachelor's degree in a directly related field, or equivalent practical experience7+ years of experience in strategy, operations, consulting, or data analysis

Analytical experience using data to tell a story and influence product direction using intermediate to advanced SQL Experience building or deploying AI/ML solutions, LLM model quality or automation in production workflows

Strong communication skills with ability to influence multiple cross-functional stakeholders and senior leadership

Experience breaking down ambiguous issues to component parts to develop solutions

Ability to design AI workflows that operate effectively within enterprise data sensitivity constraints, balancing quality and privacy principles Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Experience operating in flat, IC-heavy org structures with high individual autonomy

Demonstrated history of evaluating industry best practices and providing organizational recommendations on approaches to AI models and development

Experience in product quality, QA, or technical program management

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)
Familiarity with LLMs, AI agents, or ML evaluation frameworks

Experience working with global/remote teams