GTM Engineer
AI summary of the role
This GTM Engineer role is the 'First Customer' — building AI-native systems (agents, onboarding workflows) that power LangChain's technical support and customer success.
What you’ll do
- Architect and deploy production-grade agents using LangGraph and LangSmith to handle technical support queries and guide users through onboarding flows.
- Analyze customer friction points and build self-service AI systems to reduce support volume while improving customer experience.
- Own the full lifecycle of systems you build, proactively identifying opportunities for improvement.
- Dogfood the stack and contribute feedback to improve LangChain and LangGraph open-source frameworks.
What you’ll bring
- Deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops.
- Strong software engineer with typically 3+ years experience and at least 1 year shipping LLM systems in production.
- Self-directed 'founder' mentality — comfortable navigating ambiguity and driving high-impact problems autonomously.
- Strong coding skills in Python or TypeScript (ideally both) and ability to build end-to-end applications.
Technologies
LangChain · LangGraph · LangSmith · LLM · RAG · Python · TypeScript · agentic loops · cognitive architectures
About LangChain
Open-source and commercial platform for building, evaluating, deploying, and operating AI agents at scale.
Series B
Source and classification
Internal deployment & tooling · Evidence for this classification:
(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 are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines. You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever
More from the 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 Role: We are looking for an GTM Engineer where you won’t just be using [... source excerpt omitted ...] ilding autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it. You Will: Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows. Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience. Own the Domain: A [... source excerpt omitted ...] itectures, and own the full lifecycle of the systems you build. Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem. Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation. What we are looking for: AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have lik
Employer postings · Data from · Sources