Full-Time

Product Manager

Updated on 6/19/2025

Harvey

Harvey

501-1,000 employees

Custom AI solutions for law firms

Compensation Overview

$150k - $175k/yr

Junior, Mid, Senior

San Francisco, CA, USA

Category
Technical Product Management
Product
Required Skills
LLM
Product Management
Data Analysis
Requirements
  • 2-7 years of experience in product management and/or software engineering
  • Degree or relevant experience in CS or Engineering
  • Experience with or knowledge of AI and LLMs
  • Experience in a B2B / commercial environment
  • Demonstrated ability to ship world-class enterprise software products
  • Big picture thinking while still delivering on the details
  • Ability to use both qualitative and quantitative reasoning to communicate your ideas reasoning
  • Ability to navigate extreme ambiguity to deliver on outcomes
  • Desire to do whatever it takes to make the team successful — whether that’s doing support, testing new algorithm changes, or cleaning up tickets
Responsibilities
  • Own the lifecycle of product initiatives from inception to launch
  • Tackle unsolved AI product and eng problems — user experiences for million-token many-step agents, instant retrieval over huge TB datasets, etc
  • Gather feedback from strategic customers to inform product direction
  • Define disrupting business models, pricing packages, & other commercial standards
  • Work closely with our founders, execs, and legal research teams
  • Learn how to actually make LLMs useful for complex knowledge work
  • Help steer the growth of our product & eng organization
  • Disrupt multiple $T+ industries
Desired Qualifications
  • Early employee at a hyper-growth startup
  • Experience at world-class enterprise product orgs (ex: Brex, Ramp, Stripe, Palantir)

Harvey.ai creates custom Large Language Models (LLMs) for elite law firms to help them address complex legal challenges efficiently. Their AI technology streamlines operations and improves decision-making, exemplified by their AI chatbot developed with Allen & Overy. The company operates on a model that includes customization fees and ongoing subscriptions for support. Harvey.ai aims to transform the legal industry by enhancing the capabilities of top law firms through tailored AI solutions.

Company Size

501-1,000

Company Stage

Series D

Total Funding

$506M

Headquarters

San Francisco, California

Founded

2022

Simplify Jobs

Simplify's Take

What believers are saying

  • Harvey is in talks to raise $250M, potentially valuing it at $5 billion.
  • AI-driven contract analysis tools are gaining traction, benefiting Harvey's offerings.
  • Harvey's focus on data security is bolstered by a Security Advisory Board.

What critics are saying

  • Emerging competition from LexisNexis could rival Harvey's AI offerings.
  • Rapid valuation increases may lead to heightened investor expectations and pressure.
  • The trend towards smaller language models could challenge Harvey's LLM focus.

What makes Harvey unique

  • Harvey offers custom LLMs tailored for elite law firms' complex legal challenges.
  • The company provides a natural language interface for existing legal workflows.
  • Harvey's AI chatbot, in partnership with Allen & Overy, exemplifies significant legal work efficiencies.

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Benefits

Relocation Assistance

Growth & Insights and Company News

Headcount

6 month growth

7%

1 year growth

6%

2 year growth

79%
Best Techie
May 15th, 2025
The Tech Circus: AI, CEOs, and the Wild West of Streaming

In the latest act of the AI extravaganza, Harvey AI is making waves with a potential $250 million funding round, which would catapult its valuation to a staggering $5 billion.

Nestia
May 15th, 2025
Harvey AI raising $250M at $5B valuation

Harvey AI, a legal startup, is in advanced talks to raise over $250 million in a new funding round at a $5 billion valuation, according to sources. This round, led by Kleiner Perkins and Coatue, represents a significant increase from Harvey's previous $3 billion valuation just months ago. Sequoia Capital, an existing investor, is also expected to increase its investment.

Varenyaz
May 15th, 2025
Harvey AI's $250M Funding Round: A Game Changer for AI Innovation

Recently, Harvey AI, an innovative player in the AI landscape, has reportedly initiated discussions to raise over $250 million in a new funding round, aiming for a staggering valuation of $5 billion.

PYMNTS
Apr 14th, 2025
Ai App Startups Making Rapid Gains In Sales And Funding

Startups that build artificial intelligence (AI) applications on top of large language models (LLMs) are reportedly making rapid gains in both sales and funding. These startups are reaching as much as $200 million in annual recurring revenue in less than two years and, as a group, increased the amount of funding they attracted by 110% to reach $8.2 billion in 2024, the Financial Times (FT) reported Monday (April 14), citing data from Dealroom.co and Flashpoint. This category of AI startups includes companies like Perplexity, Synthesia,  ElevenLabs, Harvey and Sierra, according to the report

VentureBeat
Mar 20th, 2025
Small Models As Paralegals: Lexisnexis Distills Models To Build Ai Assistant

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. When legal research company LexisNexis created its AI assistant Protégé, it wanted to figure out the best way to leverage its expertise without deploying a large model. Protégé aims to help lawyers, associates and paralegals write and proof legal documents and ensure that anything they cite in complaints and briefs is accurate. However, LexisNexis didn’t want a general legal AI assistant; they wanted to build one that learns a firm’s workflow and is more customizable. LexisNexis saw the opportunity to bring the power of large language models (LLMs) from Anthropic and Mistral and find the best models that answer user questions the best, Jeff Riehl, CTO of LexisNexis Legal and Professional, told VentureBeat.“We use the best model for the specific use case as part of our multi-model approach. We use the model that provides the best result with the fastest response time,” Riehl said. “For some use cases, that will be a small language model like Mistral or we perform distillation to improve performance and reduce cost.”While LLMs still provide value in building AI applications, some organizations turn to using small language models (SLMs) or distilling LLMs to become small versions of the same model. Distillation, where an LLM “teaches” a smaller model, has become a popular method for many organizations. Small models often work best for apps like chatbots or simple code completion, which is what LexisNexis wanted to use for Protégé. This is not the first time LexisNexis built AI applications, even before launching its legal research hub LexisNexis + AI in July 2024.“We have used a lot of AI in the past, which was more around natural language processing, some deep learning and machine learning,” Riehl said