Senior Software Engineer, AI Platform

Harvey Harvey · AI Frontier · San Francisco, CA · Engineering

Senior Software Engineer for AI Platform at Harvey, focusing on building foundational agentic AI infrastructure, including context management, model routing, and evaluation frameworks for enterprise legal services. The role involves designing and implementing shared abstractions and platform-level systems to enhance agentic products and ensure reliable AI quality.

What you'd actually do

  1. Design and build abstractions and platform-level systems that improve all of Harvey’s agentic products.
  2. Own infrastructure for model integration, routing, and evaluation that helps Harvey choose and deploy the right foundation model for any given context.
  3. Build evaluation frameworks and tooling that let every team across Harvey iterate on AI quality effectively.
  4. Partner closely with product engineering teams, PMs, and design to launch cutting-edge AI products.
  5. Evaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.

Skills

Required

  • 5+ years of experience building backend systems
  • 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
  • Strong judgment about abstractions
  • Excitement about agentic AI and the infrastructure challenges of making autonomous systems reliable when the stakes are real
  • A bias toward full ownership

Nice to have

  • Staff candidates will typically have 8+ years and a track record of technical leadership across teams
  • experience building evaluation frameworks
  • working with agent/function-calling architectures
  • familiarity with legal or other high-stakes professional services domains
  • time at early-stage or hyper-growth startups where the underlying technology changes regularly

What the JD emphasized

  • enterprise-grade platform
  • AI foundation
  • model layer and agent infrastructure
  • hardest domains for AI
  • zero margin for error on accuracy
  • AI Platform team builds the foundation
  • sets the ceiling for what Harvey’s AI can do
  • Context Engineering & Agent Infrastructure
  • Evaluation Infrastructure
  • build evaluation frameworks
  • agent/function-calling architectures
  • high-stakes professional services domains

Other signals

  • AI Platform
  • Agent Infrastructure
  • Model Routing
  • Evaluation Infrastructure
  • Context Engineering