Engineering Manager, AI Platform

Harvey; San Francisco (CA); On-site; USD 272,000 - 355,000; Full time

Job summary

Harvey is redefining professional services by combining frontier AI with an enterprise‑grade platform. As we scale, you’ll lead an engineering team building the horizontal AI platform that makes Harvey’s products faster, higher quality, and more scalable.

In this role you’ll set the technical direction, collaborate with Product, Research, and Platform teams, and grow a high‑trust organization. You’ll own delivery, code quality, and ship new AI features that solve real customer problems with

Qualifications

• 2+ years of experience in a tech‑lead/software engineering management role leading ML/AI engineering teams.
• 5+ years of experience as a backend, infrastructure or ML/AI engineer.
• A track record of leading high‑performing, engaged engineering teams.
• Experience building and operating production systems powered by LLMs (agents, retrieval, eval pipelines).
• Experience building internal platforms or shared services that other engineering teams depend on, and partnering with cross‑functional stakeholders to prioritize them.
• Strong backend engineering skills in modern languages and frameworks; familiarity with distributed systems concepts.
• Sound judgment on tradeoffs among quality, latency, cost, and speed of delivery in AI systems.
• A plus: Experience with open‑source model inference and serving, document processing, search and retrieval systems, LLM observability or working with foundation model providers.

Responsibilities

• Lead and grow a team of engineers building the core AI platform that powers Harvey’s products.
• Define the roadmap for shared AI infrastructure, including model routing, open‑source and post‑trained model serving, eval and simulation infrastructure, and large‑scale document processing, embeddings, retrieval, search and citation systems.
• Partner with Product, Research, Agent Platform, and product engineering teams to understand their needs and turn recurring patterns into reusable, well‑documented platform primitives.
• Build and scale offline eval and simulation infrastructure so teams can measure quality, catch regressions, and ship AI changes with confidence.
• Drive reliability, latency, cost efficiency, and security across LLM‑powered systems, including working with model providers on capacity and rate limits.
• Evaluate and rapidly adopt new models, frameworks, and techniques, and decide what to build, buy, or adopt.
• Contribute to code and architecture reviews, unblock teams, and lead by example when needed.
• Hire, grow, and retain exceptional engineers who thrive in a high‑trust, high‑impact environment.

Skills

Tech Lead

Backend infra

ML/AI engineering

Distributed systems

Open-source ML

LLM observability

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. We have 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

Harvey is redefining what’s possible in legal work by combining cutting-edge AI with intuitive product experiences. As we scale rapidly and take on increasingly complex use cases, we’re expanding our engineering team to accelerate our ability to ship fast, delight users, and build infrastructure that scales with us.

As an Engineering Manager for AI Platform, you will lead a team of engineers building the horizontal systems that make Harvey’s AI products higher quality, faster, and more cost-efficient. This includes eval and simulation infrastructure, model routing, open-source and post-trained model serving, new-model rollouts, and the document processing systems (OCR, embeddings, retrieval, and citations) that turn any file a lawyer gives us into something Harvey can read, find, and cite. You will partner with Product, Research, and product engineering teams to turn fast-moving advances in applied AI into durable, reusable platform capabilities. You will also set the technical direction for how teams across Harvey build, test, and ship AI features.

This role is equal parts technical depth and product intuition. You’ll be trusted to make fast, high-quality decisions, work at the cutting edge of applied AI, and grow a team that embodies engineering excellence.

We move with urgency, bias toward simplicity, and expect our leaders to be hands‑on when needed. If you’re energized by ownership, decisive execution, and solving real user problems, we’d love to hear from you.

What You’ll Do

• Lead and grow a team of engineers building the core AI platform that powers Harvey’s products
• Define the roadmap for shared AI infrastructure, including model routing, open‑source and post‑trained model serving, eval and simulation infrastructure, and large‑scale document processing, embeddings, retrieval, search and citation systems
• Partner with Product, Research, Agent Platform, and product engineering teams to understand their needs and turn recurring patterns into reusable, well‑documented platform primitives
• Build and scale offline eval and simulation infrastructure so teams can measure quality, catch regressions, and ship AI changes with confidence
• Drive reliability, latency, cost efficiency, and security across LLM‑powered systems, including working with commercial and open‑source model providers on capacity, rate limits, and new capabilities
• Evaluate and rapidly adopt new models, frameworks, and techniques, and decide what to build, buy, or adopt
• Contribute to code and architecture reviews, unblock teams, and lead by example when needed
• Hire, grow, and retain exceptional engineers who thrive in a high‑trust, high‑impact environment

What You Have

• 2+ years of experience in a tech‑lead/software engineering management role leading ML/AI engineering teams, preferably in high‑growth environments
• 5+ years of experience as a backend, infrastructure or ML/AI engineer
• A track record of leading high‑performing, engaged engineering teams
• Experience building and operating production systems powered by LLMs (for example agents, retrieval, tool use, or evaluation pipelines)
• Experience building internal platforms or shared services that other engineering teams depend on, and partnering with cross‑functional stakeholders to prioritize them
• Strong backend engineering skills in modern languages and framework and familiarity with distributed systems concepts
• Sound judgment on tradeoffs among quality, latency, cost, and speed of delivery in AI systems
• A plus: Experience with open‑source model inference and serving, large‑scale document processing, search, and retrieval systems, LLM observability and eval tooling, or working directly with foundation model providers

Compensation

$272,000 - $355,000 USD

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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 [e-mail]