Staff Software Engineer, Model Infrastructure
$231k - $340k • Remote • San Francisco • FullTime
Posted 1mo ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Harvey is transforming legal and professional services by combining agentic AI, an enterprise-grade platform, and deep domain expertise. This role offers a unique opportunity to help build a generational company at an inflection point, with strong product-market fit and investor support. The team operates with intensity, ownership, and a commitment to excellence, valuing decisiveness, simplicity, and continuous improvement. If you are driven to do your best work alongside like-minded individuals, Harvey is the place to be.
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 for automated model degradation detection and intelligent traffic routing based on reliability, latency, quality, compliance, and cost.
- 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 frontier 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.