Enterprise Customer Success Manager, Harvey

$160-185k

+ Equity + Offers Uncapped Commission

Mid and Senior level

New York

More information about location

2-3 days a week in office

Domain-specific AI for legal and professional services

Job no longer available

Domain-specific AI for legal and professional services

501-1000 employees

B2BArtificial IntelligenceLegalSaaS

Job no longer available

$160-185k

+ Equity + Offers Uncapped Commission

Mid and Senior level

New York

More information about location

2-3 days a week in office

501-1000 employees

B2BArtificial IntelligenceLegalSaaS

Company mission

To help professionals develop expertise, faster.

Job

Company

Role

Who you are

Experienced professionals with a background in Enterprise SaaS, legal (big law) or top tier management consulting firms and direct experience managing large-scale technology projects
Individuals with excellent communication and strategic planning skills, capable of influencing stakeholders at various levels
Results driven candidates who are able to ruthlessly prioritize competing tasks and demanding customers seamlessly
Team players described as empathetic, committed, structured, motivated, and collaborative with a team-first mentality

What the job involves

As an Enterprise Customer Success Manager, you’ll play a critical role in guiding our clients through their journey with Harvey, and help define the future of work at top enterprises and leading Law Firms
This position is pivotal in ensuring our clients not only adopt but also derive maximum value from our technology. You'll act as a trusted advisor, deeply integrating Harvey into their business processes and workflows
Strategic Implementation: Lead the integration of Harvey into client workflows, ensuring seamless adoption and optimal use of our AI solutions
Training & Enablement: Evangelize the power of LLMs as you meet with and enable end users to adopt Harvey on a daily-basis as it becomes a “must have” product
Client Relationship Management: Serve as the primary contact for clients with a prescriptive and consultative approach and delivering a superior customer experience
Success Metrics Management: Utilize adoption rates, NPS, and other key metrics to drive strategies ensuring client satisfaction and high ROI
Advocacy and Engagement: Encourage user and stakeholder engagement, transforming them into Harvey advocates within their organizations
Customer Health Monitoring: Use analytics and feedback to maintain customer satisfaction, ensuring readiness for renewal and expansion opportunities
Feedback Loop: Relay client insights back to our internal teams, aiding in the continuous improvement of our product and services

Our take

The explosive popularity of generative AI tools has seen specialized solutions popping up for all kinds of industries. Hoping to help supercharge efficiency and productivity for legal teams, Harvey supplies generative AI that can assist with documentation, as well as aid research and optimize workflows.

Via natural language instructions, Harvey helps draft and analyze legal documents. It can also answer complex questions across large document sets, or even handle research queries that cover multiple domains in legal, regulatory and tax.

Its ability to support legal practitioners as if it's another member of the team is what makes Harvey particularly interesting. This approach has seen the company raise substantial funding, reaching Unicorn status in 2024. Funds are now being used to expand to new geographies, grow headcount and further collect and curate data to train more “domain-specific” AI models.

Kirsty

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 10 rounds)

Mar 2026

$200m

LATE VC

Oct 2025

$59m

GROWTH EQUITY VC

Total funding: $1.2bn

Company HQ

Financial District, San Francisco, CA

Leadership

Winston Weinberg

(Co-Founder & CEO)

Graduated with a Juris Doctor from the USC Gould School of Law, then spent 1 year as an Associate at O'Melveny & Myers before founding Harvey.

Gabe Pereyra

(Co-Founder & President)

Previously worked as a Research Scientist at Meta and DeepMind. Also spent a year as a Brain Resident at Google.

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