Sr. AI Enablement Engineer

Role Description

We're seeking a Sr. AI Enablement Engineer to advise on, build, integrate, and operate AI tooling for several departments within Harvey. You'll be the dedicated technical partner who turns AI capability into real workflows that teams use every day, owning the connector and MCP integrations that make those workflows possible, and work with cross-functional teams to evaluate new technologies in this space that we are seeking to adopt.

This is a hands-on technical IC role inside BizTech (Business Technology), partnering closely with teams across G&A, GTM, and Engineering. You'll spend your time evaluating vendors, prototyping AI workflows for business processes, writing integration code, and shipping tools that internal teams can extend on their own. 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.

What You'll Do

• Extend and govern AI workflows across the company.
• Own technical governance of internal AI tools.
• Own the MCP and connector roadmap for enterprise systems.
• Translate emerging AI capability into Harvey's internal roadmap.
• Run AI vendor security and privacy reviews as a structured workstream.
• Build integration prototypes and reference architectures.
• Be the technical partner of choice for G&A teams.

Qualifications

• 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.
• Strong communication and stakeholder-management instincts, especially with non-technical partners.
• Strong DevOps and operational fundamentals — CI/CD, infrastructure-as-code, secrets management, and observability.
• Demonstrated experience applying data governance & security best practices.
• Demonstrated comfort evaluating third-party vendors.
• Ability to thrive in a fast-paced, high-growth, and global environment with significant ambiguity.

Bonus Points

• 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.

Compensation

$133,500 - $200,300 USD