Staff Software Engineer, Model Infrastructure
$231k - $340k • Remote • San Francisco • FullTime
Posted 7d ago
About the job
Harvey is transforming how legal and professional services operate by combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise. This is a unique opportunity to help build a generational company at an inflection point, with strong product-market fit and investor support. The team moves fast, takes ownership, and is deeply committed to the mission, valuing decisiveness, simplicity, and continuous improvement. As a Staff Software Engineer on the Model Infrastructure team, you will lead the design and development of the systems powering all AI requests at Harvey, partnering with AI Research, Product Engineering, and external model providers to build a highly reliable, scalable, observable, and efficient platform.
Responsibilities
- Lead the design and implementation of Harvey's Model Infrastructure platform.
- Build systems for high availability, low latency, and operational excellence in AI inference.
- Design and improve the Unified Model Controller (UMC) and Model Selector platform for automated model degradation detection and intelligent traffic routing.
- Develop systems for model provisioning, capacity management, failover, and traffic engineering across multiple AI providers.
- Integrate new model providers and maintain provider APIs and SDKs to enable rapid adoption of emerging models.
- Enhance observability through health dashboards, alerting, token usage analytics, cost reporting, and end-to-end telemetry.
- Partner with Product Engineering to support model launches, experimentation, and proactive monitoring of production AI workloads.
- Drive infrastructure efficiency through capacity planning, utilization optimization, and cost visibility.
- Collaborate with AI Research to build the infrastructure foundation for future model evaluation, training, and deployment.
- Lead cross-functional technical initiatives and mentor engineers.
Requirements
- 7+ years of software engineering experience building large-scale distributed systems.
- Experience designing and operating highly available production services.
- Strong programming skills in Go, Java, Python, Rust, or C++.
- Deep understanding of distributed systems, cloud infrastructure, networking, and observability.
- Experience leading technical projects across multiple engineering teams.
- Ability to balance long-term architecture with pragmatic execution.
- Strong communication and collaboration skills.
- Passion for building foundational platforms that enable other engineering teams.