部署工程师，专业服务部（旧金山）
Deployed Engineer, Professional Services (San Francisco)
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12500万美元，我们正处于持续开发新产品、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用于自主代理改进。我们有超过1亿次每月的开源下载量，6000多家活跃的LangSmith客户，以及财富10强中有5家在生产环境中使用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。
职位描述
我们正在寻找一名已部署工程师加入我们的专业服务团队，直接与企业客户合作，构建可靠、生产级的代理。你将把模糊的企业流程转化为具体的软件规范，并指导工程团队完成相应的解决方案，或为你自己构建。你可能会花一周时间设计客户的代理架构，几周时间与他们的工程团队共同构建评估流程，或者在一个季度内嵌入他们的团队，与他们的工程师一起交付系统。你是一位在生产环境中构建过真实AI系统的人员，能够为其内部的技术权衡进行辩护。
主要职责
- 建议：代理架构设计、评估策略审查和最佳实践生产指导。
- 构建：在结果导向的合作中，与客户的工程团队共同构建整个代理开发生命周期（ADLC）。
- 嵌入：在长期合作中作为已部署工程师进入客户的团队，作为他们组织的实际成员直接交付代理系统。
- 代理工程：端到端的ADLC，架构设计，编排模式，评估
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 ROLE
We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them.
KEY RESPONSIBILITIES
- Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance.
- Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements.
- Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly.
- Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment.
- Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology.
REQUIREMENTS
- 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus.
- 2+ years of hands-on experience building and shipping production agent systems.
- Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs).
- Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory).
- Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems.
- Comfortable operating across the full spectrum from advisory to embedded delivery.
- Willing to travel up to 20% of the time.
NICE TO HAVE
- Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL.
- Experience with trace mining to drive continuous improvement loops
LOCATION
San Francisco, CA
COMPENSATION
$150,000-$215,000 base + equity
Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions.
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.