About the job
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.
Responsibilities
- 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.
Qualifications
Minimum
- 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 - 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.
Preferred
- 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.