招聘
ABOUT US
At Lang Chain, 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.
Today, Lang Chain, Lang Graph, Lang Smith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust Lang Chain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.
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. Lang Chain is a place where your contributions can shape how this technology shows up in the real world.
ABOUT THE TEAM:
- The Lang Chain Deployed Engineering
- Federal team works directly with U.S. Government customers — including the Department of Defense (DoD), Civilian Agencies, and the Intelligence Community (IC) — who are building and operating AI agents in mission-critical environments.
This is a hands-on, highly technical team that partners closely with government engineers, technical program managers, and system integrators across the full lifecycle — from pre-award technical shaping and evaluations to post-deployment advisory work in secure environments. The focus is on achieving the technical win, architecting secure and compliant agent systems, and enabling agencies to operate AI agents reliably at scale using the Lang Chain suite.
Deployed Engineers sit at the intersection of engineering, product, security, and go-to-market. You will shape how Lang Chain is adopted across classified and unclassified environments, ensuring alignment with federal compliance requirements while feeding mission-driven insights back into the platform.
ABOUT THE ROLE:
As a Deployed Engineer, you’ll work on some of the hardest problems in applied AI — not demos or experimental research, but production systems supporting real-world missions.
You’ll help defense, civilian, and intelligence customers design, deploy, and operate AI agents in secure, regulated, and high-stakes environments. The feedback loop is fast, the mission impact is tangible, and your work directly influences how AI agents are deployed across the federal landscape.
You will operate in environments that demand security, reliability, compliance (FedRAMP, IL levels, etc.), and operational rigor.
WHAT YOU’LL DO:
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Co-architect and co-build production AI agents with federal engineering teams and system integrators
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Own the technical win in federal pre-sales engagements by designing secure POCs, supporting RFI/RFP technical responses, and guiding technical evaluations
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Design architectures that meet federal security and compliance requirements (FedRAMP, DoD IL2–IL6, NIST, etc.)
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Help agencies deploy and operate agent-based applications such as mission support copilots, intelligence analysis agents, research automation systems, and multi-step operational workflows
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Advise customers post-award on architecture, scalability, observability, evaluation, and long-term roadmap decisions
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Deliver technical demos, workshops, and enablement sessions tailored to government developer and operator audiences
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Partner with security teams to navigate ATO processes and accreditation pathways
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Surface field feedback from federal use cases and contribute reusable patterns, secure deployment guides, and example code that scale across agencies
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Occasionally contribute code upstream when it meaningfully improves federal customer outcomes
WHAT YOU’LL BRING:
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3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, product engineering), ideally supporting federal or regulated customers
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Experience working with DoD, Civilian Agencies, Intelligence Community, or federal system integrators
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Strong Python and JavaScript fundamentals, with deep systems thinking
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Experience designing agent-based or LLM-powered systems beyond simple API calls, including multi-step workflows, orchestration, guardrails, and failure handling
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Familiarity with secure cloud environments (AWS Gov Cloud, Azure Government, etc.)
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Comfort operating in regulated environments with security, compliance, and documentation requirements
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Experience supporting technical evaluations, architecture reviews, and competitive down-select processes
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Ability to clearly explain technical tradeoffs to government stakeholders and build trust across engineering and program leadership
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Ownership mindset — you take responsibility for mission outcomes, not just recommendations
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Bias toward action and comfort operating in ambiguity
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Excitement about running AI agents in real-world, production federal environments — not just building demos
NICE TO HAVE:
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Active or prior U.S. security clearance (Secret, TS/SCI)
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Experience deploying AI systems in classified or air-gapped environments
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Familiarity with FedRAMP authorization processes or DoD Impact Levels (IL2–IL6)
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Experience with LLM evaluation, observability, red-teaming, or guardrails in high-assurance settings
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Hands-on experience with AWS, Azure, containers, Kubernetes, and secure networking architectures
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Experience working alongside federal system integrators (Booz Allen, SAIC, Leidos, etc.)
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Production experience with Lang Chain, Lang Graph, or similar agent frameworks
COMPENSATION & BENEFITS:
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance. 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.
Annual OTE range: $150,000–$250,000 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
·
20w ago
