Harvey

Sr. AI Enablement Engineer

San Francisco · Senior

Sponsorship not specified$134k-$200kDetected 5 days ago

Code ReviewCI/CDDevOpsOAuthLLMsAgentic AICybersecuritySalesforceERPHRISContract ManagementZendeskCadenceCommunicationNetSuite

About the role

This is a hands-on technical IC role inside BizTech (Business Technology), partnering closely with teams across G&A, GTM, and Engineering.
The ideal candidate is a senior IC engineer who is equally comfortable in a code review, a privacy lawyer's office hours, and a People Operations workflow whiteboard - and who sees making other Harvey employees more productive with AI as the actual job.

Harvey already runs AI agents in production, including automated IT support, with more functions coming online.
You'll extend that into People, Legal, Finance, and Workplace: partner with the team that owns each high-friction workflow, ship the AI-powered version, and make sure it's governed and measured.
Own technical governance of internal AI tools.
Own the pre-deployment security-review path for new AI tools, and stand up spend and usage monitoring so cost and access stay visible as adoption scales.
Own the MCP and connector roadmap for enterprise systems.
You'll harden those into production and scale the pattern across HRIS, ERP, contract management, ticketing, and knowledge bases - defining the roadmap, building the integrations, and communicating what's available.
You'll build a documented intake, a reusable AI vendor risk framework, and a clear sign-off path, partnering with Privacy, Security, and Legal.
Build integration prototypes and reference architectures. Ship working examples that internal teams can extend on their own, so you're not the bottleneck for every new workflow.
Be the technical partner of choice for G&A teams.
5+ years of software or integration engineering experience, with at least 2 years building integrations between SaaS systems (HRIS, ERP, contract management, internal platforms, communication tools).

Hands-on experience with API integration patterns, OAuth and identity, webhook architectures, and the kind of glue work that makes enterprise systems actually talk to each other reliably.
Practical experience with LLM-based applications and AI tooling - prompt design, agent workflows, retrieval, evaluation, or production integration of model APIs.
Working knowledge of the Model Context Protocol (MCP) or comparable agent-tool integration patterns.

Background that includes both a customer-facing role (Forward Deployed Engineer, Solutions Engineer, Applied AI Engineer) and an internal tooling role.
Familiarity with enterprise iPaaS platforms.
Experience inside a Business Technology, IT, or internal platform org at a high-growth B2B SaaS company.
Hands-on work with enterprise platforms like NetSuite, Workday, Ironclad, Zendesk, Salesforce, etc, including their APIs, custom development, or AI-adjacent extensions.

Demonstrated experience applying data governance & security best practices.
Ability to thrive in a fast-paced, high-growth, and global environment with significant ambiguity.

This listing is sourced directly from Harvey's careers page and normalized into a canonical job model.