Staff Software Engineer, Harvey
AI Platform
$231-340k
3 days a week in office
Domain-specific AI for legal and professional services
Be an early applicant
Domain-specific AI for legal and professional services
501-1000 employees
Be an early applicant
$231-340k
3 days a week in office
501-1000 employees
Company mission
To help professionals develop expertise, faster.
Role
Who you are
- 8+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering and a track record of technical leadership across teams
- Experience building and shipping multi-model or multi-provider AI systems in production
- Familiarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters
- A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted - and an understanding of why developer experience matters as much as raw capability
- Strong judgment about abstractions. Opinionated about good design but pragmatic about shipping incrementally
- Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real
- A bias toward full ownership: you navigate ambiguity well and don’t wait for a roadmap to start solving problems
- Bonus: experience building evaluation frameworks, working with agent/function-calling architectures, familiarity with legal or other high-stakes professional services domains, or time at early-stage or hyper-growth startups where the underlying technology changes regularly
What the job involves
- Harvey’s products all depend on a shared AI foundation: the model layer and agent infrastructure that determine the quality of work our agents deliver. Legal is one of the hardest domains for AI: documents run to hundreds of pages, matters can span millions of files, and there is zero margin for error on accuracy
- The AI Platform team builds the foundation that every product and agent team at Harvey builds upon. This team is early and there’s a lot to build: model routing, agent architecture, context management, evals. Your work here sets the ceiling for what Harvey’s AI can do
- Context Engineering & Agent Infrastructure. Build the platform-level systems for context management, session state, and memory that all of Harvey’s agents and products rely on
- Model Integration & Routing. Own the infrastructure that lets Harvey onboard new foundation models fast and route to the right one for every task - a capability every product team depends on
- Evaluation Infrastructure. Build the shared eval tooling and frameworks that let every team across Harvey measure and improve AI quality systematically
- Shared Abstractions. Create the SDKs, platform primitives, and developer tooling that make it dramatically easier for product teams to ship AI-powered features
- Design and build abstractions and platform-level systems that improve all of Harvey’s agentic products
- Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context
- Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively
- Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products
- Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge
Our take
The explosive popularity of generative AI tools has seen specialized solutions popping up for all kinds of industries. Hoping to help supercharge efficiency and productivity for legal teams, Harvey supplies generative AI that can assist with documentation, as well as aid research and optimize workflows.
Via natural language instructions, Harvey helps draft and analyze legal documents. It can also answer complex questions across large document sets, or even handle research queries that cover multiple domains in legal, regulatory and tax.
Its ability to support legal practitioners as if it's another member of the team is what makes Harvey particularly interesting. This approach has seen the company raise substantial funding, reaching Unicorn status in 2024. Funds are now being used to expand to new geographies, grow headcount and further collect and curate data to train more “domain-specific” AI models.
Kirsty
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 10 rounds)
Mar 2026
$200m
LATE VC
Oct 2025
$59m
GROWTH EQUITY VC
Total funding: $1.2bn
Company HQ
Financial District, San Francisco, CA
Leadership
Winston Weinberg
(Co-Founder & CEO)Graduated with a Juris Doctor from the USC Gould School of Law, then spent 1 year as an Associate at O'Melveny & Myers before founding Harvey.
Gabe Pereyra
(Co-Founder & President)Previously worked as a Research Scientist at Meta and DeepMind. Also spent a year as a Brain Resident at Google.
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