Sr. AI Enablement Engineer

What You'll Do

• Extend and govern AI workflows across the company into People, Legal, Finance, and Workplace; partner with teams to ship AI-powered versions that are governed and measured.
• Own technical governance of internal AI tools: define publishing process, scoping rules, review cadence for plugin and skill marketplace; own pre-deployment security-review path and stand up spend/usage monitoring.
• Own the MCP and connector roadmap for enterprise systems (HRIS, ERP, contract management, ticketing, knowledge bases): harden pilots into production, build integrations, communicate availability.
• Translate emerging AI capability (new MCP servers, agent frameworks, agentic features) into Harvey's internal roadmap with opinionated adoption recommendations.
• Run AI vendor security and privacy reviews: build documented intake, reusable AI vendor risk framework, and clear sign-off path partnering with Privacy, Security, and Legal.
• Build integration prototypes and reference architectures that internal teams can extend independently.
• Serve as the technical partner for G&A teams on workflows involving NetSuite, Workday, contract intake, vendor reviews, etc.

What You Have

• 5+ years of software or integration engineering experience, including 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 enterprise system glue work.
• Practical experience with LLM-based applications and AI tooling (prompt design, agent workflows, retrieval, evaluation, or production integration of model APIs); experience shipping real production systems that depend on models.
• Working knowledge of the Model Context Protocol (MCP) or comparable agent-tool integration patterns (read the spec and built against it at minimum).
• Strong communication and stakeholder-management skills with non-technical partners across Finance, People, Legal, IT, and Privacy.
• Strong DevOps and operational fundamentals (CI/CD, infrastructure-as-code, secrets management, observability); treat integrations and AI tools as production systems.
• Demonstrated experience applying data governance & security best practices.
• Demonstrated comfort evaluating third-party vendors (reading DPAs, reasoning about subprocessor chains, data flows, and providing go/no-go recommendations).
• Ability to thrive in a fast-paced, high-growth, 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. (APIs, custom development, or AI-adjacent extensions).