Meta is seeking an experienced Internal Audit Manager to lead independent, risk-based audits across Meta's Central Integrity, Global Operations, and Family of Apps (FOA) organizations. The ideal candidate has hands‑on experience assessing product, engineering, operational, and regulatory risks across areas such as content standards and enforcement, machine learning and large language models, data pipelines, and key metrics. The candidate will lead complex audits end to end, combining audit methodology with AI and automation to work faster and produce clear, high‑quality results.
- B.A. or B.S. degree in Computer Science, Management Information Systems, Finance, Business Administration, or a related field
- Technical acumen, project management skills, and experience communicating audit findings, risks, and recommendations in writing and in presentations to technical and non-technical stakeholders
- Experience managing time-sensitive projects to completion while balancing evolving priorities
- Demonstrated experience leveraging AI and data analytics tools such as large language models, AI assistants, and code copilots to analyze large datasets, accelerate workflows, and enhance work quality
- Critical thinking skills to evaluate, validate, and refine AI‑assisted work Experience in data analytics, content standards, or regulatory compliance
- Expertise in auditing AI systems, technology controls, and complex data pipelines
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- 6+ years of audit experience at a Big 4 firm or in internal audit functions within technology companies or in complex IT environments
- Certified Internal Auditor (CIA) and/or Certified Information Systems Auditor (CISA)
- Demonstrated ongoing AI skill development, including prompt engineering and use of AI agents, and continued learning on emerging AI technologies
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
- Proven ability to apply AI tools to improve or redesign workflows and deliver measurable impact such as efficiency gains and quality improvements