AI Engineer, Enablement
Build and teach reliable AI agent systems through customer workshops, technical content, guidance, and reference implementations. The role requires strong Python and agent-development experience plus a background delivering customer-facing technical training.
About the job
Responsibilities
- Design and deliver live, hands-on workshops that build product fluency.
- Create tutorials, reference implementations, and best-practice guides.
- Provide technical guidance and office hours to customers.
- Build internal agents and tools to automate Enablement team processes.
- Represent customer feedback to Product and Engineering.
- Track agent engineering practices and incorporate learnings into training.
Requirements
- 3+ years building LLM or agent applications, including agent architectures and evaluation strategies.
- Strong Python skills and the ability to write and debug code live with customers.
- 2+ years in a technical, customer-facing role such as Enablement, Customer Success Engineering, or Solutions Engineering.
- Experience designing and delivering live workshops and technical training programs.
- Ability to create written tutorials, documentation, and video guides.
- Exceptional presentation and communication skills for technical and enterprise audiences.
- Ability to work independently in ambiguous environments and manage multiple customer engagements.
- Willingness to travel up to 20%.
Nice to Have
- Production deployment of AI agents, especially with LangChain, LangGraph, Deep Agents, or similar frameworks.
- Experience with LLM evaluation, observability, or guardrails.
- Experience with AWS, Google Cloud, Azure, containers, and basic Kubernetes concepts.
- TypeScript or JavaScript experience.
Compensation and Benefits
- Base compensation: $150,000–$195,000 plus equity.
- Medical, dental, and vision coverage.
- Flexible vacation.
- 401(k) plan.
- Meals on in-office days in the United States.
Skills
Python, Llm Applications, Agent Architectures, Llm Evaluation, LangChain, LangGraph, Deep Agents, Langsmith, AWS, GCP, Microsoft Azure, Containers, Kubernetes, TypeScript, JavaScript
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