Head of Forward Deployed Engineering
About the role
Lead deployments and the forward-deployed engineering team for Zep AI, focusing on taking enterprise deployments from first call to production, owning technical outcomes for largest accounts, and shaping engagement models and reference architectures. Hands-on in the first year, with customer-facing responsibilities and close collaboration with founders and security/platform teams.
Responsibilities
- Own the technical outcome for our largest accounts, from the first architecture conversation through 90 days in production.
- Write code. Integration work, reference architectures, deployment tooling, and fixes in the product itself.
- Deploy Zep inside customer infrastructure across Managed, BYOK, and BYOC, and work directly with platform and security teams.
- Define the engagement model. Decide which accounts get embedded support, and set how that work is scoped and priced.
- Hire the team. You define the bar and lead the engineers you bring in.
- Reduce the custom work each deployment takes. What you build twice becomes a reference architecture or a product requirement.
- Take what you learn in production back into the roadmap. You will be in planning with the engineers who can act on what you bring.
Qualifications
- 10+ years across software engineering, forward deployed engineering, solutions architecture, or sales engineering, with several of those years as a hands-on engineer.
- Experience taking enterprise deployments from first call to production under a security review and fixed deadline.
- 3+ years leading customer-facing technical people, or a clear case for readiness to lead.
Skills
About Zep AI
The Memory Foundation For Your AI Stack
Build AI assistants that continually learn and delight users with personalized and accurate experiences. ## Memory that learns from your users Zep intelligently learns from user interactions, improving your assistant or agent's knowledge over time. Recall user facts in milliseconds, with Zep adding no latency to your prompt creation. ## Ready for Production and Scale - Granular Memory Controls: Go beyond semantic search with developer-defined rubrics for user fact relevance. - Comprehensive APIs and SDKs: Python, TypeScript, and Go SDKs, with full CRUD control of stored facts. - SOC 2 and tools for Privacy Compliance. ## Build Consistent and Correct LLM Apps Zep's Structured Output and Dialog Classification tools build on Zep's memory enabling you to build more accurate and consistent user experiences. - Extract strongly-typed data from chat history, quickly & accurately: Go beyond your LLM provider's JSON or Structured Output mode with built-in types for datetimes, floats, emails, RegEx patterns, and more. - Instantly classify conversation state: Understand user intent and emotion, segment users, and more.
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