Job Description

Meta builds technologies that help people connect, find communities, and grow businesses. The Paid, Off-Platform and Scams team within Meta’s global Integrity & Support Operations organization works to create safe, trustworthy experiences across Meta's platforms by building reliable, scalable systems that address policy violations, harmful content, and operational risk at scale. As Meta continues to expand its use of AI-assisted review and automated enforcement, human expertise remains essential to govern how these systems operate, ensure accountability, and maintain alignment with evolving integrity policies. In this role, you will drive operational programs that support integrity workflows, manage cross-functional initiatives, and help shape the systems and processes that keep Meta's platforms safe for billions of people worldwide.

In this role, you will improve the quality and scalability of support for advertisers whose content is rejected across our ads, organic, and commerce surfaces. You will serve as a subject-matter authority for the foundation of AI-assisted resolution — bringing together human-generated evaluation labels, knowledge authoring, and agent-assisted workflows so that advertisers reach faster, more accurate answers at scale. Success is measured by resolution accuracy, time to resolution, and the share of cases AI-assisted workflows resolve without human escalation.

Responsibilities

Deeply understanding the architecture and integration points of Meta's advertiser support processes, products, and policies, including ad review, ad rejection appeals, and AI-assisted resolution

• Own ongoing evaluation labeling for AI-assisted support: define label taxonomies and rubrics, produce and audit gold-standard labels, and use label quality as the ground truth for model and agent performance
• Author and maintain the knowledge that grounds agent-assisted resolution — ensuring content is accurate, policy-aligned, and machine-consumable — along with the standard operating procedures, escalation frameworks, and training materials that help operations teams apply policy consistently
• Conduct case analyses on rejected-ad support contacts to identify failure patterns, root causes, and automation opportunities, and translate findings into product, policy, and process recommendations
• Manage end-to-end program delivery, including scoping, milestone tracking, and dependency management, while aligning cross-functional stakeholders across policy, engineering, and operations on priorities and communicating risks and blockers early
• Track and report on key operational metrics such as case volume, resolution rates, policy coverage, and reviewer accuracy, translating data into actionable insights that inform leadership decisions and team strategy
• Identify opportunities to improve tooling, automation, and human-in-the-loop processes that support advertiser support decision-making at scale, and collaborate with product and engineering partners to drive those improvements

Qualifications

Currently has, or is in the process of obtaining a Bachelor's degree in a directly related field, or equivalent practical experience. Degree must be completed prior to joining Meta

• 4+ years of experience in an operational/strategic role within a technology, policy, analytical, or operations field, or equivalent consulting experience
• Experience in resolving, communicating, and presenting issues and insights to both technical and non-technical audiences
• Demonstrated experience in problem-solving with strong execution and the ability to influence and coordinate with cross-functional teams
• Analytically driven, with experience in understanding nuances and patterns within large data sets
• Experience with SQL and data visualization
• Bachelor's or an advanced degree in a relevant field Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• 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)
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience in integrity, misinformation, elections, or content policy operations
• Experience managing vendor relationships
• Experience working with global teams and Experience working with global teams and cross-cultural stakeholders