Full-Time

Executive Assistant

Confirmed live in the last 24 hours

Harvey

Harvey

501-1,000 employees

Custom AI solutions for law firms

Compensation Overview

$115k - $145k/yr

Junior, Mid

San Francisco, CA, USA

This is an in-office role based in San Francisco, with an expectation of being onsite at least three days per week, and additional days as needed based on business priorities.

Category
Executive Support
Administrative & Executive Assistance
Requirements
  • 2+ years of professional or administrative experience in a fast-paced, or high-growth environment
  • Strong organizational skills with the ability to prioritize tasks, solve problems, and operate independently in an ambiguous environment
  • Proactive and adaptable mindset, with a knack for anticipating needs and taking initiative
  • Excellent written and verbal communication skills, including the ability to craft high-quality, executive-level messaging
  • Professionalism and executive presence, with the ability to build credibility and effectively engage with senior leaders and external stakeholders
  • Collaborative and team-oriented, with a focus on fostering strong relationships across the Harvey team
  • Discreet and trustworthy when handling confidential information
Responsibilities
  • Keep things running smoothly by managing complex calendars — from exec 1:1s and team syncs to meetings with customers and prospects and company events
  • Be the go-to connector between your exec and internal teams, partners, and customers, ensuring communication is seamless and timely
  • Own the prep: draft agendas, pull together materials, track action items, and follow up to keep momentum going
  • Take the lead on booking travel — think efficient, well-planned itineraries that save time and reduce friction
  • Handle sensitive info with care, using good judgment and a high level of discretion
  • Jump in on ad hoc projects — bring structure, keep things moving, and get stuff done
  • Support with presentation and deck preparation as needed — from formatting to content coordination — to ensure executives are set up for success
  • Pitch in on general office and admin needs — no task too small when it helps the team thrive

Harvey.ai builds custom Large Language Models (LLMs) specifically for top law firms to help them tackle complex legal challenges across different areas and jurisdictions. Their AI technology streamlines operations, reduces manual tasks, and enhances decision-making processes. A notable product is their AI chatbot, developed in collaboration with Allen & Overy, which demonstrates significant efficiency improvements in legal work. Unlike many competitors, Harvey.ai focuses on bespoke AI solutions tailored to the unique needs of elite law firms, charging for both initial customization and ongoing subscription services for support and updates. The company's goal is to enhance the efficiency and accuracy of legal practices while ensuring high standards of data security, supported by a dedicated Security Advisory Board and leading security certifications.

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 raised $300 million in Series D funding, valuing the company at $3 billion.
  • Opening a London office positions Harvey to serve European clients and expand market reach.
  • LexisNexis' investment in Harvey indicates potential for cross-industry collaboration and growth.

What critics are saying

  • LexisNexis' investment could lead to conflicts of interest as they are competitors.
  • The trend of using smaller language models could challenge Harvey's focus on large LLMs.
  • International expansion, like the London office, may expose Harvey to regulatory challenges.

What makes Harvey unique

  • Harvey provides a natural language interface for legal workflows, simplifying complex tasks.
  • The company specializes in custom LLMs for elite law firms, addressing complex legal challenges.
  • Harvey's BigLaw Bench sets a benchmark for AI accuracy in legal tasks.

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Benefits

Relocation Assistance

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

52%

2 year growth

70%
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

Pulse 2.0
Feb 22nd, 2025
Harvey Raises $300M at $3B Valuation

Harvey raised $300 million in a Series D funding round at a $3 billion valuation, led by Sequoia and including investors like Coatue, Kleiner Perkins, and OpenAI Startup Fund. The company experienced 4x ARR growth and expanded to 235 customers in 42 countries, including top US law firms. The funding will enhance the platform and expand enterprise use cases. Harvey also opened a London office as its European HQ. The previous Series C round in July 2024 raised $100 million at a $1.5 billion valuation.

Harvey
Feb 13th, 2025
Harvey Raises $300M Series D Led by Sequoia

Return investors Sequoia, Kleiner Perkins, GV, Elad Gil, Conviction and OpenAI Startup Fund joined by new investors Coatue and LexisNexis at a $3B valuation.

Artificial Lawyer
Feb 13th, 2025
LexisNexis Invests $300M in Rival Harvey

LexisNexis' parent company, RELX, invested in rival AI firm Harvey through its venture arm, REV, despite Harvey's tools competing with LexisNexis products. Harvey raised $300 million at a $3 billion valuation. RELX claims the investment won't affect LexisNexis' product plans or involve cross-selling. REV aims to support innovative companies, but the strategic benefit to LexisNexis customers remains unclear.