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Mercor is an AI data company that organizes human intelligence to power the AI economy. The company operates a marketplace where millions of domain experts train frontier AI models, with over $4 million paid out daily. Mercor is a profitable Series C company valued at $10 billion.
You will own the Trust & Safety product end-to-end, responsible for fraud detection, enforcement, and the operational systems that support these functions. This role sits at the intersection of product, operations, and technical work—you'll design the multi-agent systems that score risk across the expert lifecycle, define the signals that feed detection models, and own enforcement actions and policies.
Key responsibilities include: connecting Trust & Safety decisions to long-term business health and customer trust; setting the roadmap for detection and enforcement systems; improving model accuracy by working with data science and engineering to tune detection quality while minimizing false positives and false negatives; designing the workflows and tooling that operations analysts use daily; and ensuring decisions are defensible with clear audit trails. You'll also get hands-on: writing specs and PRs, building dashboards, pulling SQL, and validating direction directly.
You'll partner across engineering, data science, operations, legal, and go-to-market teams. This is a technical, customer-facing role for someone energized by ambiguous, adversarial problems with no fixed playbook, who cares about both systems and the humans operating them, and who wants to own a high-impact product area.
Required: 5+ years in Product Management, Product Operations, Technical Program Management, Trust & Safety, Risk, Fraud, or similar technical, operationally-minded roles. Prior exposure to safety or integrity problems is a strong plus. You should be comfortable with large datasets, AI agents, and technical conversations with engineers and data scientists. Strong systems thinking, cross-functional communication, and judgment in weighing tradeoffs (false positives vs. missed fraud) are essential. Thrive in ambiguous environments and take ownership from problem definition through execution.
