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Salary: USD 231,000 - 340,000 / annual
Harvey is building an AI platform for legal and professional services, combining frontier agentic AI with enterprise-grade infrastructure. As a Staff Software Engineer on the Model Infrastructure team, you will lead the design and development of systems powering every AI request at Harvey, partnering with AI Research, Product Engineering, Infrastructure, and external model providers.
Key responsibilities include leading the design and implementation of Harvey's Model Infrastructure platform, building systems for high availability, low latency, and operational excellence in AI inference. You'll design and improve the Unified Model Controller (UMC) and Model Selector platform to automatically detect model degradations and intelligently route traffic based on reliability, latency, quality, compliance, and cost. You'll develop systems for model provisioning, capacity management, failover, and traffic engineering across multiple AI providers including OpenAI, Anthropic, Azure OpenAI, Fireworks, and Baseten.
Additional responsibilities include integrating new model providers and maintaining provider APIs and SDKs to enable rapid adoption of emerging frontier models. You'll improve observability through health dashboards, alerting, token usage analytics, cost reporting, and end-to-end telemetry. You'll partner with Product Engineering to support model launches, experimentation, and proactive monitoring of production AI workloads, and drive infrastructure efficiency through capacity planning, utilization optimization, and cost visibility.
You'll collaborate with AI Research to build the infrastructure foundation for future model evaluation, training, and deployment, and lead cross-functional technical initiatives while mentoring engineers across the organization. The role requires 7+ years of software engineering experience building large-scale distributed systems, experience designing and operating highly available production services, and strong programming skills in Go, Java, Python, Rust, or C++. Deep understanding of distributed systems, cloud infrastructure, networking, and observability is essential, along with experience leading technical projects across multiple engineering teams and ability to balance long-term architecture with pragmatic execution.
About Harvey
Legal / Compliance / Risk; AI / Data / Infrastructure — AI platform for legal and professional services work.
