採用
福利厚生
•Healthcare
•401(k)
•Equity
•Flexible Hours
必須スキル
Python
TypeScript
LLM systems
RAG
Agentic systems
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 Lang Chain 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:
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Architect Customer Agents: Design and deploy production-grade agents (using Lang Graph and Lang Smith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows.
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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.
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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.
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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 Lang Chain and Lang Graph open-source ecosystem.
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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:
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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 Lang Chain or Lang Graph.
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Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production.
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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.
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Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications.
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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:
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Expertise with Lang Smith for evaluation and monitoring.
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Experience building or maintaining open-source projects.
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A background in technical consulting, solutions engineering, or high-growth GTM teams.
Compensation:
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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.
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Salary: $160K - $180K
総閲覧数
0
応募クリック数
0
模擬応募者数
0
スクラップ
0
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LangChainについて

LangChain
Series BA platform that provides open-source frameworks and tools for engineering and deploying language model agents.
51-200
従業員数
San Francisco
本社所在地
$200M
企業価値
レビュー
3.4
3件のレビュー
ワークライフバランス
2.5
報酬
3.0
企業文化
2.8
キャリア
3.2
経営陣
2.3
35%
友人に勧める
良い点
Working with cutting-edge AI technologies like LangChain and RAG
Hands-on experience building end-to-end AI projects
Exposure to modern applied AI development
改善点
Uncertainty about long-term career prospects and employability
Projects rarely make it to production use
Lack of senior developer mentorship and guidance
給与レンジ
13件のデータ
Mid/L4
Senior/L5
Mid/L4 · Product Designer
1件のレポート
$178,619
年収総額
基本給
$155,147
ストック
-
ボーナス
-
$178,619
$178,619
面接体験
10件の面接
難易度
2.7
/ 5
期間
14-28週間
内定率
60%
体験
ポジティブ 50%
普通 40%
ネガティブ 10%
面接プロセス
1
Application Review
2
Recruiter Screen
3
Technical Assessment/Take-home
4
Technical Interview
5
Virtual Onsite/Final Round
6
Offer
よくある質問
System Design
Machine Learning/AI Knowledge
Coding/Algorithm
Technical Architecture
Behavioral/STAR
ニュース&話題
LangChain, Langflow, LiteLLM: When AI’s Foundation Code Becomes the Attack Surface - Security Boulevard
Security Boulevard
News
·
1w ago
DataCamp and LangChain Partner to Launch AI Engineering Learning Track - Business Wire
Business Wire
News
·
3w ago
Finally made it ugghhhh
https://preview.redd.it/61yq8yyinnrg1.png?width=462&format=png&auto=webp&s=1f821e417ef14ac8d60ecd0714297886a81586fa Hey I am 3rd year CS undergrad from Lower NIT, I started out my journey seriously in 2nd year by learning MERN nd stuff did an internship at the end of 4th sem (which was unpaind and work from home). During summer vacation I realised this web dev stuff is not for me and switched to learning ML nd boy I loved this domain (maybe since I sucked at web dev i was under pres
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3w ago
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19
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23
LangChain Releases Comprehensive Agent Evaluation Checklist for AI Developers - mexc.com
mexc.com
News
·
3w ago