Meta is seeking a Strategic Risk Program Manager to lead privacy risk governance and program strategy across the company's global product and infrastructure portfolio. In this role, you will define and operationalize frameworks for identifying, assessing, and mitigating privacy risks at scale, partnering with legal, policy, engineering, and product teams to embed risk management practices into how Meta builds and ships products. You will drive cross-functional alignment on privacy risk posture, influence executive decision-making, and shape the long-term direction of Meta's privacy risk programs in a complex and rapidly evolving regulatory environment.

Qualifications:

8+ years of experience in privacy program management, risk management, or compliance program management within a technology company or regulated industry Experience designing and operationalizing risk governance frameworks, including risk assessment methodologies, control libraries, and escalation structures Experience driving cross-functional programs with full accountability across legal, policy, engineering, and product stakeholders in ambiguous and complex environments Experience communicating privacy risk strategy and program status to executive audiences through written materials, briefings, and governance forums Experience translating privacy regulatory requirements (such as GDPR, CCPA, or equivalent frameworks) into operational program requirements and controls Familiarity with privacy engineering concepts such as data minimization, purpose limitation, privacy by design, and data flow mapping Experience working within a privacy accountability or consent order compliance program at a large-scale technology company Recognized privacy certification such as CIPP, CIPM, or CIPT Experience building or scaling privacy risk tooling, intake processes, or risk register systems across a large organization 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 ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)