AI工程师，赋能
AI Engineer, Enablement
关于我们
在LangChain，我们的使命是让智能代理无处不在。我们构建了现实世界中代理工程的基础，帮助开发者从原型过渡到可信赖的生产级AI代理。我们最初是广泛采用的开源工具，现已发展出一个平台，用于大规模构建、评估、部署和运营代理。
在IVP、Sequoia、Benchmark、CapitalG和Sapphire Ventures的B轮融资中筹集了1.25亿美元，我们正处于继续开发新产品、增长加速的阶段，所有团队成员都能对我们的产品和协作方式产生重要影响。LangChain是一个你可以塑造这项技术如何在现实世界中呈现的地方。
如今，我们的平台包括LangSmith（可观测性、评估、部署、车队和沙盒）、我们的开源框架（LangChain、LangGraph和Deep Agents），以及新推出的LangSmith Engine用于自主代理优化。我们有超过1亿次每月的开源下载量，6000多名活跃的LangSmith客户，以及财富100强中有5家在生产中使用LangSmith（占财富500强的35%），包括Klarna、Clay、Coinbase、Workday、Lyft、Cloudflare、Harvey、Rippling、Vanta、LinkedIn、Monday.com、Nvidia和Bridgewater的团队。
关于团队
使能团队通过现场培训、动手研讨会和技术内容，帮助客户建立对代理工程和LangSmith平台的实际熟练度，这些内容可以超越一对一的时间限制。
关于职位
你将为客户提供如何使用LangChain生态系统构建可靠代理的技术基础，通过讲师主导的研讨会、书面内容和参考实现，教授他们的团队有效使用LangChain、LangGraph、Deep Agents和LangSmith。我们与更广泛的GTM组织紧密合作，确保每位客户都具备独立构建所需的技能和信心。
你是一位真正构建过代理系统的人，能够为其权衡做出辩护，并且真心热爱教学，无论是面对50名工程师的现场研讨会，还是与一名陷入困境的开发人员进行调试会。你还将构建使使能团队自身更高效的内部代理和工具。
你将负责
- 设计并提供动手实践的现场研讨会，提升真实的产品熟练度，而不仅仅是熟悉度
- 创建使能资源（教程、参考实现、最佳实践指南）
查看英文原文
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.