Senior Product Operations Manager, Evaluation

Harvey
San FranciscoPosted 21 January 2026

Job Description

Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewWe’re looking for a technical, systems-minded operator to build and scale the evaluation engine behind Harvey’s platform. As we expand globally, ensuring our models behave reliably, accurately, and jurisdictionally correctly is mission-critical—and evaluation complexity is increasing 10x.As a member of our Product Operations team, you’ll work closely with Applied Legal Researchers, Product, Engineering, AI Research, and human data providers to operationalize evaluation methodologies and embed them into our product development lifecycle. You’ll create the workflows, systems, and tooling that make evaluation a first-class product capability at Harvey.This is a high-ownership role for someone who thrives in ambiguity, loves building structure from ambiguity, and wants to help scale the evaluation infrastructure of a global AI company.What You’ll DoBuild and scale the systems that power model and product evaluations across HarveyEmbed evaluation workflows and readiness checkpoints into the product development lifecycleCreate the single source of truth for evaluation status, results, history, and launch readinessTurn Expert-designed evaluation methodologies into scalable, repeatable operational processesManage relationships with human data vendors and ensure evaluation quality meets legal standardsWork with Engineering and Research to improve evaluation tooling, automation, and dashboardsDrive evaluation readiness for major product and model launches across geographies and jurisdictionsDocument and operationalize evaluation governance as complexity increasesHelp define how Harvey ensures model accuracy, reliability, and trust at global scaleWhat You Have4–7+ years in technical program management, product operations, research operations, or evaluation/benchmarking rolesExperience working with ML/AI evaluations, benchmarking frameworks, or scientific workflowsComfort with statistical methodologies and SQL or Python, or similar tools to interpret evaluation dataAbility to work deeply with legal experts and operationalize complex evaluation methodologiesStrong cross-functional coordination skills across Product, Engineering, Research, and data providers/vendorsHigh attention to detail and a bias toward clarity, rigor, and reproducibilityAbility to navigate extreme ambiguity and bring order to complex systemsStrong communication skills and comfort translating technical nuance for diverse stakeholdersDesire to do whatever it takes to make evaluation systems successful—from writing documentation to diagnosing pipeline issuesBonus PointsExperience in legal tech or working with domain experts in regulated industriesExperience managing human data providers or human-in-the-loop evaluation pipelinesBackgro ... (truncated, view full listing at source)
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