Full-Time

User Operations Manager

Confirmed live in the last 24 hours

Harvey

Harvey

501-1,000 employees

Custom AI solutions for law firms

No salary listed

Mid, Senior

London, UK

Category
Customer Experience & Support
Customer Experience
Customer Support
Required Skills
Data Analysis
Requirements
  • 4+ years of experience in a customer support or user operations role, with at least 2 years in a leadership capacity.
  • Proven experience managing and scaling support teams in a fast-paced environment.
  • Strong ability to balance strategic thinking with hands-on execution in daily support operations.
  • Experience supporting enterprise and mid-market customers, with a focus on white-glove service and operational efficiency.
  • Deep familiarity with Freshdesk or similar customer support platforms.
  • Excellent problem-solving skills and a data-driven approach to decision-making.
  • Strong communication and collaboration skills, with experience working cross-functionally across Product, Engineering, and Customer Success teams.
  • A passion for customer experience and a drive to continuously improve support processes and outcomes.
Responsibilities
  • Lead and manage a small team of User Operations Specialists, fostering a culture of customer-first problem-solving and operational excellence.
  • Ensure best-in-class customer support, particularly for enterprise customers, by refining processes and optimizing support workflows.
  • Drive efficiency and scalability in customer support by developing self-service resources, knowledge bases, and automation strategies.
  • Monitor team performance and KPIs, ensuring alignment with company-wide goals for customer satisfaction and operational effectiveness.
  • Collaborate with Product, Engineering, and Go-to-Market teams to ensure smooth escalation processes and feedback loops for product improvements.
  • Oversee support tooling and infrastructure, particularly leveraging Intercom, to enhance customer interactions and streamline operations.
  • Analyze customer support data to identify trends, improve processes, and enhance overall user experience.
  • Hire, train, and develop team members, ensuring a high level of expertise and continuous learning within the team.

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 is in talks to raise $250 million, boosting its valuation to $5 billion.
  • The legal technology market is rapidly growing, offering expansion opportunities for Harvey.
  • Significant financial backing from investors like Sequoia and OpenAI supports technological advancements.

What critics are saying

  • Emerging competition from LexisNexis could challenge Harvey's market position.
  • High valuation and funding rounds may lead to increased investor pressure.
  • Investment from competitor RELX could create strategic challenges for Harvey.

What makes Harvey unique

  • Harvey offers a natural language interface for legal workflows, simplifying complex tasks.
  • The company builds custom Large Language Models for elite law firms globally.
  • Harvey's AI chatbot, in partnership with Allen & Overy, enhances legal work efficiency.

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Benefits

Relocation Assistance

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

1%

2 year growth

70%
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