Jobs
About Lang Chain:
At Lang Chain, our mission is to make intelligent agents ubiquitous. We provide the agent engineering platform and open source frameworks developers need to ship reliable agents fast.
Our open source frameworks, Lang Chain and Lang Graph, see over 90+ million downloads per month and help developers build agents with speed and granular control. Lang Smith offers observability, evaluation, and deployment for rapid iteration, enabling teams to transform LLM systems into dependable production experiences.
Lang Chain is trusted by millions of developers worldwide and powers AI teams at companies like Replit, Clay, Cloudflare, Harvey, Rippling, Vanta, Workday, and more.
About the role
In person 5 days/week in San Francisco, CA or New York, NY
We're building purpose-built infrastructure for running AI agents. Unlike traditional web apps, agents run for long durations, collaborate asynchronously with humans and other agents, and need to survive failures mid-execution. Lang Smith Deployments is the runtime that makes this work, with durable checkpointing, fault-tolerant orchestration, and horizontal scaling, deployed across cloud and self-hosted environments.
We're looking for a Senior Backend Engineer to work on this system. While the focus is on backend development, strong familiarity with Kubernetes (K8s), Terraform (Tf), and other DevOps tooling is highly preferred.
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Design distributed queue and worker systems that handle concurrent agent execution, background tasks, and multi-agent coordination across horizontally scalable infrastructure
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Own core data infrastructure — state persistence, atomic job claiming, connection management, and schema evolution
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Collaborate on architectural decisions, ensuring solutions are scalable and robust.
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Ship resumable streaming infrastructure so clients can disconnect and reconnect mid-execution without losing state
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Instrument and monitor production systems — tracing, metrics, and alerting to keep the platform healthy
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Participate in on-call rotations and own incident response for the runtime
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Create and maintain technical documentation, including system design and operational runbooks.
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Contribute to and extend open-source Lang Graph, which is used by thousands of developers to build agent applications
How to be successful in this role
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4+ years of professional backend engineering experience
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Strong proficiency in Go and/or python
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Experience with distributed systems — conensus mechanisms, queueing, state machines, and/or workflow orchestration
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Experience with scaling and sharding databases in high throughput environments
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Familiarity with Kubernetes, infrastructure-as-code, and at least one major cloud platform
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Strong communication skills and ability to work cross-functionally on a small team
Compensation & Benefits:
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We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations.
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Annual salary range: $175,000-$225,00 USD
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About LangChain

LangChain
Series BA platform that provides open-source frameworks and tools for engineering and deploying language model agents.
51-200
Employees
San Francisco
Headquarters
$200M
Valuation
Reviews
3.4
3 reviews
Work Life Balance
2.5
Compensation
3.0
Culture
2.8
Career
3.2
Management
2.3
35%
Recommend to a Friend
Pros
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
Cons
Uncertainty about long-term career prospects and employability
Projects rarely make it to production use
Lack of senior developer mentorship and guidance
Salary Ranges
9 data points
Mid/L4
Mid/L4 · Product Designer
1 reports
$178,619
total / year
Base
$155,147
Stock
-
Bonus
-
$178,619
$178,619
Interview Experience
10 interviews
Difficulty
2.7
/ 5
Duration
14-28 weeks
Offer Rate
60%
Experience
Positive 50%
Neutral 40%
Negative 10%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Assessment/Take-home
4
Technical Interview
5
Virtual Onsite/Final Round
6
Offer
Common Questions
System Design
Machine Learning/AI Knowledge
Coding/Algorithm
Technical Architecture
Behavioral/STAR
News & Buzz
LangChain: $125 Million Raised To Advance Agent Engineering Platform - Pulse 2.0
Source: Pulse 2.0
News
·
19w ago
LangChain Raises $125M in Series B, Hits $1.25B Unicorn Valuation - WebProNews
Source: WebProNews
News
·
19w ago
Sequoia backs AI agent tools LangChain at $1.3b valuation - Tech in Asia
Source: Tech in Asia
News
·
19w ago
LangChain becomes unicorn with $1.25B valuation in Series B - The Tech Buzz
Source: The Tech Buzz
News
·
19w ago