Senior Software Engineer, AI Platform
AI summary of the role
Harvey is hiring a Senior Software Engineer for its AI Platform team, which builds the shared foundation (model routing, agent architecture, context management, evals) that all Harvey products depend on.
What you’ll do
- 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.
What you’ll bring
- 5+ years of experience building backend systems, with at least 1+ year focused on AI/ML engineering.
- 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.
- A track record of building internal platforms, SDKs, or shared infrastructure that other engineering teams actually adopted.
Technologies
backend systems · AI/ML engineering · multi-model AI systems · context management · session state · memory systems · SDKs · evaluation frameworks · agent/function-calling architectures
About Harvey
Agentic AI platform purpose-built for elite law firms and in-house legal teams to automate research, drafting, document review, and complex matter workflows.
Private Late
Source and classification
Internal deployment & tooling · Evidence for this classification:
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’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
More from the 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’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 h [... source excerpt omitted ...] taff candidates will typically have 8+ years 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 ab
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