
AI assistant for legal professionals
Senior Product Manager, Data & Retrieval
薪酬
$178,500 - $241,500
必备技能
Search and retrieval systems
Data platform management
RAG frameworks
LLMs
Embeddings
Hybrid search
WHY HARVEY
At 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 OVERVIEW:
Harvey is building the AI platform for the world’s top legal and professional services teams. Our users rely on fast, accurate access to external legal data to perform research that underpins their most important work. As we scale, our Data & Knowledge organization sits at the center of this mission—turning raw, fragmented information into intelligent systems that power research and reasoning at global scale.
Our Data Team is responsible for ingesting, structuring, understanding, and retrieving millions of documents across jurisdictions, formats, and domains. Whether public or private, offline or online, our mission is to organize the world’s legal information and make it accessible, reliable, and useful.
We’re looking for a Product Manager with deep search, retrieval, and data platform expertise to lead the next generation of Harvey’s data engine as we 100× our capabilities. You will shape the strategy, roadmap, and architecture behind the systems that make advanced reasoning possible. The team owns end-to-end RAG (retrieval-augmented generation) pipelines across domains such as case law, legislation, tax code, and IP law across 50+ jurisdictions. As generation quality continues improving, retrieval quality has become the new frontier—and one of Harvey’s highest priorities.
If you’re passionate about large-scale data problems, complex information retrieval, and building the backbone of cutting-edge AI systems, we’d love to meet you.
WHAT YOU'LL DO:
-
Drive the roadmap and strategy for Harvey’s “Data Factory”, ensuring we scale our data 100x through new platforms that build the ‘legal index’ of the world
-
Work with internal operations and external data providers to methodically expand coverage, accelerate execution, and improve dataset quality.
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Own and evolve Harvey’s end-to-end data architecture—from ingestion and transformation to storage, indexing, and retrieval—ensuring performance, reliability, and scalability for LLM-powered products.
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Partner with Applied AI engineers to build and optimize retrieval systems, embeddings, search models, and evaluation frameworks.
-
Architect and oversee large-scale ingestion pipelines that aggregate, normalize, and continuously update millions of heterogeneous legal documents across global jurisdictions.
-
Collaborate cross-functionally with Product Engineering, Applied AI, Research, and Platform teams to deliver high-quality production systems that support reasoning, summarization, and legal research workflows.
WHAT YOU HAVE:
-
5+ years of experience building or managing search, retrieval, recommendation, or data platforms at scale.
-
Experience working with complex, heterogeneous, or domain-specific datasets with structured + unstructured data.
-
Understanding of modern retrieval methods, including hybrid search (lexical + vector), dense retrieval, re-ranking, embeddings, chunking strategies, and index optimization.
-
Hands-on experience with LLMs or RAG frameworks (evaluation, grounding, hybrid pipelines, query rewriting, LLM-as-a-judge, retrieval metrics).
-
Ability to partner with engineers on technical architecture, with enough depth to challenge assumptions, propose solutions, and influence design.
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A product mindset for search—balancing user needs, domain complexity, and system constraints to propose high-leverage improvements.
COMPENSATION RANGE:
$178,500 - $241,500 USD
PLEASE FIND OUR CA APPLICANT PRIVACY NOTICE HERE https://www.harvey.ai/legal/california-applicant-privacy-notice.
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
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关于Harvey AI

Harvey AI
Series BHarvey AI develops artificial intelligence software for legal professionals, providing AI-powered tools for legal research, document analysis, and workflow automation.
51-200
员工数
Boca Raton
总部位置
$1.5B
企业估值
评价
10条评价
4.0
10条评价
工作生 活平衡
3.8
薪酬
2.7
企业文化
4.2
职业发展
3.1
管理层
4.0
72%
推荐率
优点
Supportive team and management
Flexible hours and remote work options
Great collaboration and teamwork
缺点
Limited career advancement opportunities
Compensation and pay issues
High workload and occasional long hours
薪资范围
1个数据点
Senior/L5
Senior/L5 · Software Engineer
1份报告
$243,846
年薪总额
基本工资
$187,574
股票
-
奖金
-
$243,846
$243,846
面试评价
1条评价
难度
3.0
/ 5
时长
14-28周
录用率
100%
体验
正面 100%
中性 0%
负面 0%
面试流程
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
常见问题
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Culture Fit
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