部署工程师（夏洛特）
Deployed Engineer (Charlotte)
关于公司
在LangChain，我们的使命是让智能代理无处不在。我们构建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，现已发展为一个平台，用于构建、评估、部署和大规模运行代理。
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有意义的影响。LangChain是一个你可以塑造这项技术在现实世界中呈现方式的地方。
如今，我们的平台包括LangSmith（可观测性、评估、部署、集群和沙盒）、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。我们拥有超过1亿次每月的开源下载量，6000多家活跃的LangSmith客户，以及5家财富100强企业使用LangSmith进行生产（占财富500强企业的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
已部署工程团队直接与正在构建和运行AI代理的公司合作，帮助将想法和原型转化为团队可以依赖的系统。
这是一个注重实践、高度技术性的团队，与客户工程师紧密合作，贯穿整个生命周期，从售前评估到售后咨询工作。重点在于实现技术上的成功，共同设计代理架构，并帮助客户使用LangChain套件可靠地大规模运行代理。
已部署工程师位于工程、产品和市场进入的交汇点，塑造LangChain在实际应用中的采用方式，并将现实世界的洞察反馈到平台上。
关于职位
已部署工程师……你将解决应用AI中最困难的问题——不是演示，不是研究，而是真实团队在生产环境中依赖的系统。反馈循环迅速，影响显而易见，你所做的工作直接影响现实世界中AI代理的构建方式。
职责
- 与客户工程团队共同架构和构建生产级AI代理
- 在售前阶段主导技术成功
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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 Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.
ABOUT THE ROLE
The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
WHAT YOU’LL DO
- Co-architect and co-build production AI agents with customer engineering teams
- Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
- Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
- Advise customers post-sale on architecture, best practices, and roadmap-level decisions
- Run technical demos, trainings, and workshops for developer audiences
- Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
- Occasionally contribute code upstream when it meaningfully improves customer outcomes
WHAT YOU’LL BRING
- 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
- Strong Python, JavaScript and systems fundamentals
- Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
- Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
- Can explain technical tradeoffs clearly and build trust with developer audiences
- Take responsibility for outcomes, not just recommendations
- Have a bias toward action and enjoy figuring things out as you go
- Are excited about operating AI agents in production, not just building demos
NICE TO HAVE’S:
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
- Worked with LLM evaluation, observability, or guardrails
- Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- Have shipped and operated production software and are comfortable owning systems under real-world constraints
COMPENSATION
Annual OTE range: $150,000–$250,000 USD
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.