Why This Job is Featured on The SaaS Jobs
Applied AI Engineer roles are becoming a defining function inside modern SaaS products, particularly where customers expect AI to be embedded directly into core workflows rather than offered as a separate add on. This listing stands out because it is clearly centered on productionizing LLM driven systems within an enterprise platform used by professional services teams, a segment where reliability, auditability, and domain constraints shape how SaaS is built.
From a SaaS career perspective, the work described maps to durable skills: designing evaluation loops, running experimentation, and turning research level techniques like RAG into maintainable product capabilities. That combination of applied ML, full stack delivery, and platform thinking is widely transferable across AI native SaaS, especially as more products move toward multi step agentic workflows and model orchestration across providers.
This role fits engineers who prefer owning end to end outcomes, from data and model behavior through to user facing workflow design. It is well suited to professionals who want their AI work to be tied to real customer usage and who are comfortable partnering closely with non engineering domain experts to define what “correct” looks like in a SaaS product.
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 — not incrementally, but end-to-end. 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 500+ customers in 50+ 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 is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.
At Harvey, the future of professional services is being written today — and we’re just getting started.
Role Overview
As an Applied AI Engineer on the Engineering team at Harvey, you will own and lead engineering projects across our various product lines. We are looking for individuals who have worked across the stack on incredible products and have experience building products where machine learning models are a core component.
This role is based in New York City, NY. We use an in-person work model and offer relocation assistance to new employees.
What You'll Do
Conduct data collection, experimentation, and analysis to drive algorithmic development for RAG and multi-step AI pipelines.
Zero-to-one product development: rapidly prototype, evaluate, integrate, and test new product features in close partnership with our legal team.
Develop new AI native workflows: implement streaming, long-running tasks, procedural UX, etc. for new AI tasks, finding the balance between state-of-the-art and pragmatism.
Representative Projects
Partner with our legal team to design and implement a method for evaluating the correctness of document citations. Use this to build a large dataset of ground-truth citations and then improve our core citation algorithm. You can read about some of our work on evaluation and citations here (1, 2, 3).
Make targeted improvements to our RAG pipelines to improve answer quality for user questions over corpuses of complex data, like massive banks of spreadsheets or Japan’s tax code.
Design and build systems that leverage state-of-the-art LLMs from multiple model providers, including custom models.
Work across the stack and with our legal team to create seamless multi-step AI workflows for complex legal tasks, like corporate merger due diligence.
What You Have
7+ years of experience (post-BS/MS) in an engineering role.
Experience with shipping a scaled and impactful product powered by machine learning: how to use offline datasets, online experiments, and recent research to build simple and high performance systems. Prior experience with LLMs and retrieval pipelines is not required.
Track record of shipping reliable products and a strong attention to detail.
Experience building backend platforms that can support multiple product lines.
Grit - experience working at early-stage startups is a plus.
Compensation Range
$238,000 – $312,000 USD
Please find our CA applicant privacy notice here.
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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 interview-help@harvey.ai.
