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.
Today, LangChain, LangGraph, LangSmith, and Agent Builder are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain 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. LangChain is a place where your contributions can shape how this technology shows up in the real world.
The LangChain 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 LangChain suite.
Deployed Engineers sit at the intersection of engineering, product, security, and go-to-market. You will shape how LangChain is adopted across classified and unclassified environments, ensuring alignment with federal compliance requirements while feeding mission-driven insights back into the platform.
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.
Co-architect and co-build production AI agents with federal engineering teams and system integrators
Own the technical win in federal pre-sales engagements by designing secure POCs, supporting RFI/RFP technical responses, and guiding technical evaluations
Design architectures that meet federal security and compliance requirements (FedRAMP, DoD IL2–IL6, NIST, etc.)
Help agencies deploy and operate agent-based applications such as mission support copilots, intelligence analysis agents, research automation systems, and multi-step operational workflows
Advise customers post-award on architecture, scalability, observability, evaluation, and long-term roadmap decisions
Deliver technical demos, workshops, and enablement sessions tailored to government developer and operator audiences
Partner with security teams to navigate ATO processes and accreditation pathways
Surface field feedback from federal use cases and contribute reusable patterns, secure deployment guides, and example code that scale across agencies
Occasionally contribute code upstream when it meaningfully improves federal customer outcomes
3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, product engineering), ideally supporting federal or regulated customers
Experience working with DoD, Civilian Agencies, Intelligence Community, or federal system integrators
Strong Python and JavaScript fundamentals, with deep systems thinking
Experience designing agent-based or LLM-powered systems beyond simple API calls, including multi-step workflows, orchestration, guardrails, and failure handling
Familiarity with secure cloud environments (AWS GovCloud, Azure Government, etc.)
Comfort operating in regulated environments with security, compliance, and documentation requirements
Experience supporting technical evaluations, architecture reviews, and competitive down-select processes
Ability to clearly explain technical tradeoffs to government stakeholders and build trust across engineering and program leadership
Ownership mindset — you take responsibility for mission outcomes, not just recommendations
Bias toward action and comfort operating in ambiguity
Excitement about running AI agents in real-world, production federal environments — not just building demos
Active or prior U.S. security clearance (Secret, TS/SCI)
Experience deploying AI systems in classified or air-gapped environments
Familiarity with FedRAMP authorization processes or DoD Impact Levels (IL2–IL6)
Experience with LLM evaluation, observability, red-teaming, or guardrails in high-assurance settings
Hands-on experience with AWS, Azure, containers, Kubernetes, and secure networking architectures
Experience working alongside federal system integrators (Booz Allen, SAIC, Leidos, etc.)
Production experience with LangChain, LangGraph, or similar agent frameworks
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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