Engineering Manager, Model Infrastructure

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 enables you to guide architectural decisions and mentor senior engineers.
• Experience operating highly available production services with strong reliability and operational excellence.
• Experience building platforms that require scalability, observability, automation, and cost optimization.
• Strong cross-functional leadership skills with the ability to partner effectively across Engineering, Research, Product, and external vendors.
• Excellent communication skills and the ability to influence technical strategy across organizations.
• A passion for building teams and developing engineering talent.

Nice to Have

• Experience with AI infrastructure, LLM serving, or machine learning platforms.
• Experience working with multiple model providers such as OpenAI, Anthropic, Azure OpenAI, Fireworks, Baseten, or open-source model ecosystems.
• Experience building inference platforms, model gateways, traffic routing systems, or policy-based serving infrastructure.
• Experience with Kubernetes, cloud infrastructure, distributed systems, and large-scale observability platforms.
• Experience supporting GPU infrastructure, model training platforms, or ML infrastructure.
• Familiarity with data platforms and technologies such as Spark, Kafka, Flink, Airflow, or Iceberg.
• Experience leading organizations through periods of rapid growth and technical transformation.

Compensation