AI Engineer, Enablement

You'll set the technical foundation for how customers learn to build reliable agents with the LangChain ecosystem, teaching their teams to work effectively with LangChain, LangGraph, Deep Agents, and LangSmith through instructor-led workshops, written content, and reference implementations. We work closely with the broader GTM org to make sure every customer has the skills and confidence to build independently.

You are someone who's built real agent systems, can defend the tradeoffs in them, and genuinely loves teaching, whether that's a live workshop for 50 engineers or a debugging session with one stuck developer. You'll also build the internal agents and tools that make the Enablement team itself more efficient.

Design and deliver live, hands-on workshops that build real product fluency, not just familiarity

Create enablement assets (tutorials, reference implementations, best-practice guides) that scale beyond individual sessions

Offer technical guidance or office hours as questions come up

Build internal agents and tools that streamline how the Enablement team operates, automating processes so the team scales efficiently

Act as the voice of the customer inside LangChain, feeding friction points back to Product and Engineering

Stay current on agent engineering practices and fold what you learn into what you teach

Technical:

3+ years building LLM/agent applications, with experience designing agent architectures and evaluation strategies

Strong Python, comfortable writing and debugging code live, in front of a customer

Customer-facing & Education:

2+ years in a technical, customer-facing role (Enablement, Customer Success Engineering, Solutions Engineering, or similar), including experience designing and delivering live workshops

A genuine excitement for teaching, the kind where you'd rather leave a customer more capable than impressed

Demonstrated ability to create and deliver high-quality technical training programs, including live workshops, written tutorials, documentation, and video guides

Exceptional presentation and communication skills, with the ability to explain complex technical concepts to diverse audiences, from individual developers to enterprise stakeholders

Additional:

Comfortable operating independently in ambiguity and managing several customer engagements at once

Curiosity to stay at the forefront of agent engineering in industry to identify evolving trends and quickly incorporate learnings into customer enablement materials

Willing to travel up to 20% of the time

You've deployed AI agents in production, especially using LangChain, LangGraph, Deep Agents, or similar frameworks

Hands-on experience with LLM evaluation, observability, or guardrails

Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts

TypeScript/JavaScript in addition to Python

Compensation:

$150-$195k + equity

Compensation Philosophy:

We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.