Engineering Manager, AI Platform

Harvey • San Francisco, CA

3d • $272,000 - $355,000

About The Position

Harvey is hiring an Engineering Manager for its AI Platform team to lead and scale engineers building foundational systems that power AI across its products. The platform includes model access and routing, agent and workflow orchestration, evaluation frameworks, tool and context infrastructure, and observability for reliable LLM-powered products at scale. The role partners with Product, Research, and product engineering teams to turn advances in applied AI into durable, reusable platform capabilities, while setting technical direction for how teams build, test, and ship AI features. It combines technical depth with product intuition and expects decisive execution, ownership, and hands-on leadership when needed.

Requirements

• At least 2 years of experience in a software engineering management role leading platform, infrastructure, or full-stack product engineering teams.
• At least 5 years of experience as a backend, infrastructure, or full-stack engineer.
• A track record of leading high-performing, engaged engineering teams.
• Experience building and operating production systems powered by LLMs, such as agents, retrieval, tool use, or evaluation pipelines.
• Experience building internal platforms or shared services that other engineering teams depend on, and partnering with cross-functional stakeholders to prioritize them.
• Strong backend engineering skills in modern languages and frameworks such as Python, Go, or Node, and familiarity with distributed systems concepts.
• Sound judgment balancing quality, latency, cost, and speed of delivery in AI systems.

Nice To Haves

• Experience with durable job execution frameworks.
• Experience with MCP or other tool and context protocols.
• Experience with LLM observability and evaluation tooling.
• Experience working directly with model providers.
• Experience leading teams in high-growth environments.

Responsibilities

• Lead and grow a team of engineers building the core AI platform.
• Define the roadmap for shared AI infrastructure, including model gateways and routing, agent orchestration, tool calling, prompt and context management, and long-running job execution.
• Partner with Product, Research, and product engineering teams to turn recurring needs into reusable, well-documented platform primitives.
• Build and scale evaluation, testing, and monitoring systems to measure quality, catch regressions, and help teams ship AI features confidently.
• Drive reliability, latency, cost efficiency, and security across LLM-powered systems, including collaborating with model providers on capacity, rate limits, and new capabilities.
• Evaluate and rapidly adopt new models, frameworks, and techniques, deciding what to build, buy, or adopt.
• Contribute to code and architecture reviews, unblock teams, and lead by example when needed.
• Hire, grow, and retain exceptional engineers.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed