Lead Forward Deployed Engineer

Zep is the memory and context layer for AI agents. As Lead Forward Deployed Engineer, you'll embed with customer engineering teams to integrate Zep into their production agent systems: diagnosing context-quality failures, designing memory architectures around their data, and shipping the integrations that make their agents actually work in the wild.

This is an applied AI engineering role with a customer surface. We're not looking for ML researchers or data scientists. We're looking for engineers who have already lived through the messy reality of taking an agent from demo to production.

What you'll do

• Own end-to-end delivery for strategic deployments: scope, design, build, rollout, stabilize.
• Embed with customer engineers to integrate Zep into real systems: data, APIs, auth, infra.
• Ship production code: integrations, reference implementations, performance and reliability fixes.
• Help level up the FDE function: coach newer FDEs on execution, review designs and code when useful, and capture repeatable patterns.

What we're looking for

• 6+ years of production engineering. You can own both architecture and implementation, and you've shipped systems that real customers depend on.
• Hands-on AI agent / LLM application experience. You've shipped a non-trivial agentic system to production. That is, not a prototype, not a thin wrapper over a chat-completion API. We expect concrete examples: multi-turn agent loops with tool calling, retrieval and context pipelines you tuned against real failures, eval harnesses you built to catch regressions, or production memory and state systems for agents.