Senior Engineering Manager, Model Infrastructure
Harvey
- Location
- San Francisco
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
- Salary
- $272k – $355k/yr
- Posted
- 3h ago
Skills
About this role
Why Harvey 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. Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you. At Harvey, the future of professional services is being written today — and we’re just getting started.
Role
Overview As the Engineering Manager for Model Infrastructure, you'll lead the team responsible for the platform powering every model request across Harvey. You'll partner closely with AI Research, Product Engineering, Infrastructure, and external AI providers to ensure our platform remains reliable, scalable, and cost-efficient as our business grows. Model Infrastructure is one of Harvey's most strategic engineering organizations. Every product capability—from chat experiences and agents to document workflows and future reasoning systems—depends on this platform. Over the next several years, the team will evolve beyond operating third-party models to building the infrastructure that enables Harvey to train, evaluate, deploy, and operate our own frontier AI models. This role offers the opportunity to shape the technical foundation of Harvey's AI platform and build an organization that will power the company's next phase of growth.
What You'll Do
Lead and grow a high-performing team of software engineers responsible for Harvey's Model Infrastructure platform. Define the technical roadmap for model reliability, scalability, and operational excellence. Build highly reliable systems for model provisioning, capacity management, failover, and incident response across multiple AI providers. Own Harvey's multi-provider model platform, including provider integrations, SDK upgrades, API migrations, and onboarding new model providers. Drive the evolution of our Unified Model Controller (UMC) and Model Selector platform to automatically detect degraded models and intelligently route traffic based on health, latency, quality, compliance, and cost. Improve observability through health dashboards, alerting, token usage analytics, cost reporting, and end-to-end model telemetry. Partner with Product Engineering to support new model launches, capacity planning, experimentation, and proactive production monitoring. Lead initiatives to improve inference efficiency, reduce infrastructure costs, and increase model utilization across providers. Build the infrastructure foundation for Harvey's future model training efforts, including data pipelines, model operations, training environments, and AI platform capabilities. Partner with executive leadership on long-term AI infrastructure strategy and vendor relationships. Recruit, mentor, and develop exceptional engineering talent while fostering a culture of technical excellence and operational ownership. What You Have 8+ years of software engineering experience, including multiple years managing high-performing engineering teams. Experience leading teams responsible for large-scale distributed systems or cloud infrastructure. Strong technical background that