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Harvey

Builds AI software for lawyers

Manager – Customer Experience Knowledge & Enablement

Customer Education & TrainingConfirmed live in the last 24 hours
Full-time$144k - $216k /yrHybrid

About the Job

Requirements

  • At least 8 years of experience across knowledge management, support enablement, education, trust and safety, or a related function, including experience building or leading a team and owning a system rather than a program.
  • At least 4 years of experience managing teams in a high-volume environment serving enterprise customers.
  • Demonstrated experience architecting knowledge for service at scale, including building a knowledge system serving a large user and AI agent population and explaining its architecture decisions and outcomes.
  • A point of view on enablement in an AI-assisted support organization, including how the competency bar and training change when agents handle first-line support and specialists handle complex cases.
  • Track record of owning a consolidation or platform migration that retired fragmented surfaces and moved an organization onto one system.
  • Experience launching, managing, and improving knowledge or training platforms, with measurable operational improvement.
  • Ability to define success metrics, instrument ramp, quality, and resolution outcomes, and use the findings to prioritize investment.
  • Instructional design range and judgment to choose learning formats and adapt content for different audiences, tenure levels, and learning preferences.
  • Experience working in fast release cycles and rapidly adapting content as products and processes evolve.
  • Deep familiarity with AI-assisted support workflows and enabling agents and specialists to handle complex technical customer issues.
  • Experience building content for AI systems and people, or a clear point of view on how shared knowledge bases change when consumed by both.
  • Ability to partner across Product, Engineering, AI, and GTM to get work built and adopted without owning the technology.
  • Strong communication skills and the ability to establish credibility for the team's work across the organization.

Responsibilities

  • Own the knowledge infrastructure strategy end to end, including architecture, consolidation from fragmented surfaces, governance, platform decisions, and content for enablement and training, product best practices, troubleshooting, and product support.
  • Architect knowledge so it is structured, retrievable, and reliable for human and AI consumers.
  • Own support competency standards, defining readiness from onboarding through mastery, how it is measured, and how readiness is maintained as the product changes weekly.
  • Own the quality system as the diagnostic layer on top of the infrastructure, routing incorrect, missing, or unfindable knowledge back into the platform rather than a training backlog.
  • Build the release-to-readiness loop with Product and Product Ops and convert shipped changes into organizational readiness ahead of ticket volume.
  • Design a balanced learning strategy, selecting instructor-led sessions, self-paced modules, written documentation, short-form video, peer learning, and in-workflow guidance appropriate to each audience, content type, and urgency.
  • Build and lead the team that maintains the system, hire ahead of need, set a high bar, and scale team capability with the organization.
  • Measure downstream outcomes including specialist ramp time, attainment of performance targets, speed to competency on new releases, resolution quality, and deflection through self-service and agent-handled resolution; combine quantitative metrics with structured specialist feedback, create targeted action plans, and report effectiveness to leadership.
  • Use AI to generate and maintain content, detect staleness and gaps from ticket signals, and automate enablement work that does not require a person; continually raise the team's leverage.
  • Partner with the AI Support team, Engineering, Product, and GTM Enablement to ensure the knowledge layer serves dependent surfaces, and own agent-facing content.

Desired Qualifications

  • Experience supporting a legal, regulated, or otherwise high-stakes customer base.

About the Company

Harvey

Builds AI software for lawyers

Harvey builds AI software made specifically for legal work, used by lawyers at large law firms and corporate legal departments. It became one of the first generative AI tools rolled out across a major law firm when Allen & Overy gave it to its lawyers worldwide in 2023. Lawyers use Harvey to research legal questions, draft and review contracts, and run due diligence across large sets of documents, with answers grounded in their firm's own files and trusted legal sources. Firms pay through enterprise subscriptions, and Harvey can tailor its workflows to practice areas such as litigation and mergers. Harvey was founded in 2022 with early backing from the OpenAI Startup Fund and is based in San Francisco.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$1.8B
Headquarters
San Francisco, CA
Founded
2022

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