AI Engineer, Enablement

LangChain; Tampa (FL); On-site; USD 150,000 - 195,000; Full time

Job summary

LangChain in the United States is seeking an Enablement specialist to set the technical foundation for teaching customers to build reliable agents with LangChain, LangGraph, Deep Agents, and LangSmith through live workshops, tutorials, and reference implementations.

You’ll lead hands-on sessions for engineering teams, write scalable training content, and provide expert guidance, while partnering with Product and Engineering. Travel up to 20% is expected.

Qualifications

• 3+ years building LLM/agent applications and designing agent architectures.
• Strong Python and live-coding ability in front of customers.
• 2+ years in a technical, customer-facing role with experience delivering live workshops.
• Exceptional presentation and communication skills for diverse audiences.
• Willing to travel up to 20% of the time.

Responsibilities

• Design and deliver live, hands-on workshops that build product fluency.
• Create enablement assets (tutorials, reference implementations, guides) that scale.
• Offer technical guidance or office hours as questions come up.
• Build internal agents and tools to improve Enablement team efficiency.
• Represent the customer perspective to Product and Engineering.
• Stay current on agent engineering practices and incorporate learnings into training.

Skills

LLM/agent architectures

Python

Tools

LangChain

LangGraph

Deep Agents

LangSmith

Job description

About Us

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

About Us

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

About The Team

The Enablement team helps customers build real fluency with agent engineering and the LangSmith platform through live training, hands‑on workshops, and technical content that scales beyond 1:1 time.

About The Role

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.

What You’ll Do

• 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

What You’ll Bring

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

Nice to Have

• 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.

Benefits

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in‑office days in the US and more.