AI評価の品質を統括し、評価ガイドラインの策定や契約弁護士の評価品質管理を担当します。6年以上の関連経験が必須であり、評価データの信頼性を高めるための測定指標設計や運用プロセスの標準化を行います。製品およびエンジニアリングチームと連携し、評価結果を意思決定に活用できるレベルまで引き上げる役割です。評価運用チームに所属し、実務的なQAやデータ分析を通じて評価品質の維持・向上を主導します。
At Harvey, we’re transforming how legal and professional services operate. 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. We have 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 moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
We’re looking for a senior operator to own the quality bar behind Harvey’s human evaluations. As we scale globally, the volume of eval work is growing 10x, but volume only matters if the output is trusted. This role makes Human Data’s signal decision-grade: rigorous, calibrated, and reproducible enough that Product, Engineering, and AI Research act on it to ship.
As a member of our Evaluation Operations team, you’ll work alongside our Evaluation Operations Manager (who runs throughput and coordination) and partner closely with Applied Legal Researchers, Product, Engineering, and AI Research. You'll set the standard for what "good" looks like across eval data and methodology, and certify that results are sound before teams rely on them, building the stakeholder trust that lets EPD act on the signal.
Own the quality bar for Harvey’s human evaluations: define what “good” looks like for eval data and make outputs decision-grade for EPD
Author and maintain the evaluation guidelines, instructions, benchmarks, and gold references that contract attorneys work from, and serve as the arbiter on ambiguous or disputed judgments
Standardize and streamline rubric and evaluation design into repeatable templates and one documented methodology, partnering with Applied Legal Research (ALR), who supplies feature-specific legal depth
Own contract-attorney quality: onboarding, calibration training, inter-rater reliability, and the feedback loop that keeps judgment consistent across attorneys and over time
Define and maintain the failure-mode / error taxonomy that turns raw eval results into a structured, prioritized signal Product and ALR can act on
Run QA on vendor and contract-attorney deliverables against a defined bar before results inform a launch decision
Ensure the quality bar holds across jurisdictions and non-English geographies as coverage expands
Establish one standard, documented way to analyze eval results, and build lightweight operational dashboards to track rater capability and eval-program health
Support ALR in a review step that certifies an evaluation is sound before it scales to contract attorneys
Partner with ALR and Analytics to determine where human eval aligns with online signal and where it can provide expanded insights
6+ years in product operations, research operations, evaluation/QA operations, or quality program management
A track record of owning quality inputs (guidelines, instructions, benchmarks, QA procedures) for complex, expert-driven or human-in-the-loop work
Experience onboarding, training, and calibrating a distributed pool of expert raters, annotators, or reviewers, and running the feedback loop that improves their quality over time
Enough grounding in measurement concepts (calibration, inter-rater reliability, sampling, rubric design) to independently set up and own quality yourself
Comfort with interpreting evaluation data, natively or with AI tool support
A record of scaling and streamlining quality processes under shipping pressure, with a bias toward documentation and reproducibility over one-off analysis
Ability to work deeply with domain experts (e.g., ALR / lawyers) and translate nuanced judgment into repeatable, documented standards
Strong cross-functional coordination across Product, Engineering, Research, ALR, and data providers/vendors
Clear communicator who can build credibility and trust with stakeholders
Bias to action and high ownership, from writing the guideline to auditing a vendor batch line by line
Experience in legal tech or working with domain experts in regulated industries
Experience owning quality across multiple markets, languages, or jurisdictions
Built calibration, inter-rater reliability, or capability-tracking systems for annotation or evaluation pipelines
Experience transitioning evaluation work in-house or otherwise improving evaluation ROI
Familiarity with LLM-as-judge / automated evaluation used alongside human eval
Early employee at a hyper-growth startup, or experience at a world-class product or platform operations org
$155,400 - $233,200 USD
#LI-CD1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
