Product Risk Program Manager

Meta; Menlo Park, Seattle, Washington, New York (CA, WA, District of Columbia, NY); On-site; USD 150,000 - 200,000; Full time

Job summary

Meta is seeking a Product Risk Program Manager to join the Assurance Assessments within the Product Risk Program Manager team. The role focuses on evaluating risk determinations for accuracy and ensuring privacy decisions cover all relevant risks and mitigations.

You will collaborate with product, engineering, legal, and risk SMEs, and may engage auditors. A strong background in compliance programs and auditing is essential to define structure in ambiguity and drive progress.

Qualifications

• Experience in risk management within product teams or tech companies.
• Ability to translate risk findings into actionable guidance for stakeholders.
• Proven cross-functional coordination across legal, product, and engineering.

Responsibilities

• Assess risk determinations for accuracy and completeness.
• Ensure privacy decisions include all relevant risks and mitigations.
• Lead remediation efforts and track mitigation progress.
• Engage product, engineering, legal, and risk SMEs; interface with external auditors if needed.
• Develop and maintain risk frames, playbooks, and governance processes.

Skills

Risk management

Program management

Cross-functional collaboration

Structured risk assessments

Stakeholder communication

AI tools integration

Privacy & data governance

Regulatory compliance

Ambiguity navigation

Data analysis & automation

Job description

The Product Risk Program Manager will join the Assurance Assessments within the Product Risk Program Manager team. This role is responsible for assessing risk determinations for their accuracy. More specifically, this role will be responsible for ensuring that approved privacy decisions include all relevant risks and related mitigations. Additionally, the PRPM in this role will help ensure that required mitigations are appropriately implemented. In conducting these reviews and any needed remediations, PRPMs will engage key internal stakeholders including product, engineering, legal, and risk subject matter experts. PRPMs may also need to engage external stakeholders such as an auditor or assessor. A strong candidate for this role will have experience with compliance programs and auditing processes and be able to navigate ambiguity by defining structure, clarifying priorities, and driving progress without complete information.

• 2+ years of experience in risk management, program management, compliance, trust and safety, or a related field within a technology or product organization
• Experience conducting structured risk assessments and translating findings into actionable recommendations for product or business stakeholders
• Experience managing cross-functional programs, including coordinating across legal, policy, engineering, and operations teams to drive alignment and resolution
• Experience developing and maintaining program documentation such as risk registers, playbooks, decision frameworks, or process runbooks
• Experience communicating complex risk topics in writing to both technical and non-technical audiences, including leadership-level stakeholders
• Experience with product risk, trust and safety, or regulatory compliance programs at a large-scale consumer technology or social media company
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Familiarity with privacy, data governance, or content integrity risk domains and the regulatory frameworks that govern them
• Demonstrated ability to build and iterate on risk frameworks or governance processes in ambiguous, fast-moving product environments
• Experience using data analysis or workflow automation tools to monitor risk signals, track mitigation progress, or improve program efficiency
• 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)