Automation Program Manager, Legal and Compliance Operations

Legal and Compliance Operations is seeking an Automation Program Manager to help us automate high-volume review at scale across Legal and Compliance workflows. Our workflows run on a composite of LLM-based decisioning, rules-based logic that encodes policy directly, and signals drawn from reporter history, content matching and behavioral patterns. Automation now carries a substantial share of enforcement volume, which means its quality determines both the legal risk we mitigate and the experience of the rights holders, regulators and people who depend on these decisions.

As an Automation Program Manager, you will own the measured quality of assigned automations. Half of the role is forward motion: taking an automation from where it performs today to where the operational plan requires, through iteration on prompts, rules and signal thresholds. The other half is regression response: when reliability, correctness, precision or recall degrades, you find out why and drive it back.

An effective candidate in this role is rigorous about measurement, comfortable working across all three automation types, and able to tell a genuine regression apart from a shift in what is arriving.

• 2+ years of relevant experience in data annotation, labeling, quality assurance, or content review operations, including time spent close to automated decision output
• Experience with guideline accuracy and inter-rater agreement, including diagnosing why qualified reviewers disagree
• Working knowledge of Python and SQL, with experience pulling a dataset, computing precision and recall, and segmenting results to locate where loss is concentrated
• Experience reading and reasoning about conditional logic to trace how a decision was reached
• Experience working with large operational datasets in a notebook environment
• Investigative approach to metric movement, identifying cause rather than the explanation that fits
• Experience communicating results clearly, including reporting a metric that has not moved or a regression that is not yet explained
• Experience in adversarial or fraud-adjacent domains where the reviewed population actively shifts
• Experience with rules engines, decision tables, routing logic or classifier thresholds
• Experience coordinating with vendor or cross-functional reviewer pools
• 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 or expertise in legal and compliance operations, or trust and safety
• Experience iterating on prompts with measured before-and-after results
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)