Harvey9 дней назад

Senior Product Operations Manager, Evaluation Quality

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15 708 ₽медиана по профессии

Product Manager · 21 вакансий с указанной зарплатой

5 667половина предложений: 12 153–17 952250 000

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Полная занятостьУдалёнка

Обязанности

01Own the quality bar for Harvey’s human evaluations: define what “good” looks like for eval data and make outputs decision-grade for EPD
02Author 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
03Standardize 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
04Own contract-attorney quality: onboarding, calibration training, inter-rater reliability, and the feedback loop that keeps judgment consistent across attorneys and over time
05Define and maintain the failure-mode / error taxonomy that turns raw eval results into a structured, prioritized signal Product and ALR can act on
06Run QA on vendor and contract-attorney deliverables against a defined bar before results inform a launch decision
07Ensure the quality bar holds across jurisdictions and non-English geographies as coverage expands
08Establish one standard, documented way to analyze eval results, and build lightweight operational dashboards to track rater capability and eval-program health
09Support ALR in a review step that certifies an evaluation is sound before it scales to contract attorneys
10Partner with ALR and Analytics to determine where human eval aligns with online signal and where it can provide expanded insights

016+ years in product operations, research operations, evaluation/QA operations, or quality program management
02A track record of owning quality inputs (guidelines, instructions, benchmarks, QA procedures) for complex, expert-driven or human-in-the-loop work
03Experience onboarding, training, and calibrating a distributed pool of expert raters, annotators, or reviewers, and running the feedback loop that improves their quality over time
04Enough grounding in measurement concepts (calibration, inter-rater reliability, sampling, rubric design) to independently set up and own quality yourself
05Comfort with interpreting evaluation data, natively or with AI tool support
06A record of scaling and streamlining quality processes under shipping pressure, with a bias toward documentation and reproducibility over one-off analysis
07Ability to work deeply with domain experts (e.g., ALR / lawyers) and translate nuanced judgment into repeatable, documented standards
08Strong cross-functional coordination across Product, Engineering, Research, ALR, and data providers/vendors
09Clear communicator who can build credibility and trust with stakeholders
10Bias to action and high ownership, from writing the guideline to auditing a vendor batch line by line