Harvey
Manager, CX Knowledge & Enablement
New York · Senior
Sponsorship not specified$144k-$216kDetected 1 day ago
Agentic AILeadershipCommunication
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odds of building a lasting career here
59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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About the role
- most of what it needs to become does not.
- You'll define what this function is responsible for, what it deliberately isn't, and the roadmap that gets it there.
- The foundation exists; most of what it needs to become does not.
Responsibilities
- Own the knowledge infrastructure strategy end to end: the architecture, the consolidation path off our current fragmented surfaces, the governance model, and the platform decisions.
- This covers the full content surface: enablement and training, product best practices, troubleshooting, and product support.
- Own the standards for support competency at Harvey: what "ready" means from onboarding through mastery, how it's measured, and how readiness is maintained against a product that changes weekly.
- Own the quality system as the diagnostic layer on top of the infrastructure. Where knowledge is wrong, missing, or unfindable it should route back into the platform rather than into a training backlog.
- Build the release-to-readiness loop with Product and Product Ops and the mechanism that converts what's shipping into organizational readiness ahead of the ticket volume.
- Build and lead the team that maintains the system: hire ahead of need, set a high bar, and scale the team's capability in step with the organization it serves.
- Treat the team's own leverage as something to keep raising.
- Partner with the AI Support team, Engineering, Product, and GTM Enablement to make sure the knowledge layer serves every surface that depends on it, and own the agent-facing content itself.
- You're rebuilding the function for where support is going, not porting what worked before.
Requirements
- Demonstrated experience in architecting knowledge to be serviceable at scale.
- You've built a knowledge system serving a large user and AI agent population, and you can speak to the architecture decisions and what they bought you.
Compensation
- $144,000 - $216,000 USD
Benefits
- Design a balanced, audience-appropriate learning strategy.
- Choose the right mix of instructor-led sessions, self-paced modules, written documentation, short-form video, peer learning, and in-workflow guidance for each audience, type of content, and level of urgency.
- 8+ years across knowledge management, support enablement, education, trust & safety, or a related function, including experience building or leading a team and owning a system rather than a program.
Company info
- Demonstrated experience in architecting knowledge to be serviceable at scale. You've built a knowledge system serving a large user and AI agent population, and you can speak to the architecture decisions and what they bought you.
- A point of view on what enablement becomes when agents handle the first line and specialists only see the hard cases: how the competency bar moves, what training is for, and which parts of the traditional playbook stop applying. You're rebuilding the function for where support is going, not porting what worked before.
- Track record of owning a consolidation or platform migration that retired fragmented surfaces and got an organization onto one system.
- Experience launching, managing, and improving knowledge or training platforms, with measurable operational improvement to show for it.
- Strong instructional design range, including the judgment to choose the right format for each learning need and to adapt content for different audiences, tenure levels, and learning preferences.
- Experience working in fast release cycles and adapting content rapidly as products and processes evolve.
- Deep familiarity with AI-assisted support workflows and what it takes for an agent and a specialist to handle complex technical customer issues with confidence.
- Experience building content for AI systems as well as people, or a clear point of view on what changes when both are consuming the same knowledge base.
- Strong cross-functional instincts, you know how to partner across Product, Engineering, AI, and GTM to get the right things built and adopted without needing to own the technology yourself.
- Excellent communication skills and the presence to establish credibility for your team's work across the organization.
This listing is sourced directly from Harvey's careers page and normalized into a canonical job model.