AI Engineer, Enablement
LangChain · Remote
MeritLog read this listing from LangChain's Ashby job board and last checked it on September 8, 2026.
Source: the employer's Ashby job board. Open the original listing for current details.
Job details
- Work model
- Remote
- Salary
- Not listed by source
- Location
- New York, NY
Hiring context
How this role compares at LangChain
LangChain has 107 live roles in MeritLog’s catalog across 7 job families, and 48 of them are in engineering. 63 of those listings publish a pay range, a disclosure rate of 59%.
LangChain concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What you'd 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 they're asking for
- 3+ years building LLM/agent applications, with experience designing agent architectures and evaluation strategiesExperience
- Strong Python, comfortable writing and debugging code live, in front of a customerSkill
- 2+ years in a technical, customer-facing role (Enablement, Customer Success Engineering, Solutions Engineering, or similar), including experience designing and delivering live workshopsExperience
- A genuine excitement for teaching, the kind where you'd rather leave a customer more capable than impressedSkill
- Demonstrated ability to create and deliver high-quality technical training programs, including live workshops, written tutorials, documentation, and video guidesSkill
- Exceptional presentation and communication skills, with the ability to explain complex technical concepts to diverse audiences, from individual developers to enterprise stakeholdersSkill
- Comfortable operating independently in ambiguity and managing several customer engagements at onceSkill
- Curiosity to stay at the forefront of agent engineering in industry to identify evolving trends and quickly incorporate learnings into customer enablement materialsSkill
- Willing to travel up to 20% of the timeSkill
- You've deployed AI agents in production, especially using LangChain, LangGraph, Deep Agents, or similar frameworksSkillPreferred
- Hands-on experience with LLM evaluation, observability, or guardrailsSkillPreferred
- Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes conceptsSkillPreferred
- TypeScript/JavaScript in addition to PythonSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
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. 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.
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