GTM Engineer

Posted 2 Days Ago
Be an Early Applicant
San Francisco, CA
In-Office
160K-180K Annually
Mid level
Information Technology • Software • Database
The Role
Build and ship production-grade autonomous customer agents using LangChain/LangGraph to deflect support cases and automate onboarding. Own technical roadmap, design agentic architectures, dogfood the stack, and deliver end-to-end AI-native onboarding and self-service systems.
Summary Generated by Built In

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 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: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, 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 likely already built with LangChain or LangGraph.

  • Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production.

  • Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously.

  • Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications.

  • Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture.

Nice to Haves:

  • Expertise with LangSmith for evaluation and monitoring.

  • Experience building or maintaining open-source projects.

  • A background in technical consulting, solutions engineering, or high-growth GTM teams.

Compensation:

  • We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance.

  • Salary: $160K - $180K

Top Skills

Agentic Architectures
Langchain
Langgraph
Langsmith
Llms
Open-Source
Prompting
Python
Rag
Typescript
Am I A Good Fit?
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The Company
123 Employees

What We Do

LangChain is the platform for building reliable agents. Our products power top engineering teams — from fast-growing startups like Lovable, Mercor, and Clay to global brands including AT&T, Home Depot, and Klarna.

LangGraph is a low-level orchestration framework for building controllable agents and long-running workflows. It’s used in production by teams at Replit, Uber, LinkedIn, GitLab, and more.

LangSmith offers unified evaluation and monitoring to help developers debug, evaluate, and improve their agents at scale.

LangChain provides hundreds of integrations and composable components, making it easy to connect with the latest models, tools, and databases — with minimal engineering overhead.

Together, these tools help teams build, deploy, and manage enterprise-grade agents, faster.

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