AI Engineer – Enablement

This is a fully remote position, open to applicants in District of Columbia, +6 more states.

📋 Description

• Design and facilitate engaging, practical workshops that enhance customer understanding of agent engineering and the LangChain ecosystem.

• Develop tutorials, reference implementations, and guidelines reflecting best practices.

• Offer technical support and hold office hours for assistance.

• Create internal agents and tools to optimize Enablement operations and automate workflows.

• Represent the customer perspective within LangChain by relaying challenges to Product and Engineering teams.

• Keep abreast of the latest trends in agent engineering and integrate insights into customer enablement resources.

• Instruct customers on utilizing LangChain, LangGraph, Deep Agents, and LangSmith.

• Work collaboratively with the broader GTM organization to empower customers to build independently.

⛳️ Requirements

• Over 3 years of experience in developing LLM/agent applications, including designing agent architectures and evaluation strategies.

• Proficient in Python; capable of writing and debugging code in real-time during customer interactions.

• At least 2 years in a technical, customer-facing role such as Enablement, Customer Success Engineering, or Solutions Engineering.

• Proven experience in designing and conducting live workshops.

• Ability to create and implement technical training programs, encompassing live workshops, written tutorials, documentation, and video resources.

• Outstanding presentation and communication abilities; adept at elucidating complex technical ideas to varied audiences.

• Capacity to work autonomously in uncertain situations and manage multiple customer engagements simultaneously.

• Eagerness to remain informed about the evolving practices and trends in agent engineering.

• Willingness to travel up to 20% of the time.

• Nice to have: experience in deploying production AI agents, particularly with LangChain, LangGraph, Deep Agents, or comparable frameworks.

• Nice to have: hands-on experience with LLM evaluation, observability, or guardrails.

• Nice to have: familiarity with AWS, GCP, Azure, containers, and foundational Kubernetes concepts.

• Nice to have: proficiency in TypeScript/JavaScript alongside Python.

🏝️ Benefits

• Equity

• Medical coverage

• Dental coverage

• Vision coverage

• Flexible vacation

• 401(k) plan

• Meals provided on in-office days in the US

• Flexible work arrangement (Remote)