Why This Job is Featured on The SaaS Jobs
Frontier AI is moving from product features into the operating fabric of SaaS companies, and this role sits at that inflection point. Rather than building customer-facing functionality, it focuses on making internal systems and workflows AI-capable across functions like Legal, Finance, People, and IT. In a company already running AI agents in production, the work reflects a maturing phase of enterprise SaaS where reliability, access control, and measurable impact matter as much as novel capability.
For a SaaS career, the standout value is the blend of integration engineering and operational governance. Owning connector and MCP patterns across core SaaS tools builds durable expertise in APIs, identity, observability, and change management, the skills that keep modern SaaS stacks coherent at scale. The remit also includes structured vendor evaluation and privacy and security review paths, which is increasingly central as SaaS teams adopt third-party AI tooling and need defensible controls.
This role suits an experienced individual contributor who prefers hands-on building while acting as a technical partner to non-engineering stakeholders. It will fit someone who enjoys ambiguous problem spaces, can translate between business process and system design, and is motivated by making other teams more effective through dependable internal platforms.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
Why Harvey
At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.
This is a rare chance to help build a generational company at a true inflection point. With 1500+ customers in 60+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.
Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.
At Harvey, the future of professional services is being written today — and we’re just getting started.
Role Overview
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. 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. Define the publishing process, scoping rules, and review cadence for the plugin and skill marketplace. 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. Several MCP integrations are already piloted against core 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.
Translate emerging AI capability into Harvey's internal roadmap. Track new MCP servers, agent frameworks, and new agentic features across the platforms in use, and make a clear, opinionated call on what to adopt, ignore, or wait on for relevant use cases.
Run AI vendor security and privacy reviews as a structured workstream. AI-adjacent vendor evaluations land on BizTech regularly and are handled ad hoc today. 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. Sit next to Finance on a NetSuite workflow, next to People on a Workday-flavored automation, next to Legal on a contract intake flow, and next to Privacy on a vendor review. Translate fluently in every direction.
What You Have
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. You don't need to have trained a model; you do need to have shipped something real that depends on one.
Working knowledge of the Model Context Protocol (MCP) or comparable agent-tool integration patterns. If you haven't shipped MCP yet, you've at minimum read the spec and built something against it.
Strong communication and stakeholder-management instincts, especially with non-technical partners — you can be the most technical person in a Privacy review and the most pragmatic person in an engineering one in the same afternoon, sitting between Finance, People, Legal, IT, and Privacy without losing context.
Strong DevOps and operational fundamentals — CI/CD, infrastructure-as-code, secrets management, and observability. You treat the integrations and AI tools you ship as production systems: version-controlled, monitored, and safe to change without breaking the teams that depend on them.
Demonstrated experience applying data governance & security best practices.
Demonstrated comfort evaluating third-party vendors — reading DPAs, reasoning about subprocessor chains, asking the right questions about data flows, and translating findings into clear go/no-go recommendations for the business.
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
Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [here].
#LI-RB1
Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai
