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Meta

Product Risk Program Manager, Evidencing and Monitoring

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What they do

A Risk Engineer is responsible for identifying, analyzing and minimizing risks often associated with construction or resource extraction projects. May work for insurance companies, or engineering firms.

$147,120 / year median in California

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Job Description

The Product Risk Program Manager, Evidencing and Monitoring will join the Assessor Engagement team within the Product Risk Program Manager organization. This role is responsible for coordinating and providing evidence for Privacy Review Safeguards, owning Key Control Indicator (KCI) creation, maintenance, and monitoring, and ensuring data quality and reproducibility across all compliance artifacts. The Product Risk Program Manager, Evidencing and Monitoring will provide embedded technical context and continuity to navigate challenges including historical gaps, data deprecations, and high request volumes. They will build and maintain complex data pipelines and queries (Presto/Hive) to support external regulatory requests, produce reproducible evidence packages, and defend data methodologies during regulatory engagements. This role bridges the gap between engineering and compliance, requiring both technical depth (SQL, Python, Hack) and the ability to communicate findings clearly to external regulators and internal stakeholders including product, engineering, legal, and risk subject matter experts. Additionally, this role is responsible for conducting various audit types, assessing risk determinations for accuracy, including ensuring that approved privacy decisions include all relevant risks and related mitigations. The ideal candidate will have experience with compliance programs and auditing processes and be able to navigate ambiguity by defining priorities, clarifying requirements, and driving progress with incomplete information.
Qualifications:
4+ years of experience with regulatory/compliance/audit exposure in an analytical role Familiarity with SQL, scripting languages (e.g., Python), and AI for compliance Demonstrated analytical thinking and problem-solving experience Able to explain and create code and objects as needed (e.g., Python) for evidence and tooling Ability to work cross-functionally between engineering and various POC teams Detail-oriented, conscientious focus for data quality and privacy processes Experience communicating cross-functionally, particularly in the area of consensus-building and persuasion Ability to work with tight, inflexible regulator deadlines Flexibility to respond and change quickly to vague, uncertain, frequently changing requests Regulator mindset and the ability to see from the perspective of the requestor 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) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Experience with Privacy/Risk 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) Experience engaging with external regulators or in an external engagement role Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Familiarity with adjacent compliance spaces such as Competition, Integrity, and Security Knowledge of Meta products and principles