LangChain
AI
DeployedEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Deployed Engineer at LangChain. Skills: Deployed Engineering, AI agents, LLM-powered applications, Production systems, Customer interaction, Technical architecture, LangChain suite. Co-architect and co-build production AI agents with customer engineering teams. Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations”
What You'll Achieve.
Make intelligent agents ubiquitous; Build the foundation for agent engineering in the real world; Help developers move from prototypes to production-ready AI agents; Achieve the technical win; Help customers operate agents reliably at scale; Shape how LangChain is adopted in the field; Feed real-world insights back into the platform; Build systems that real teams depend on in production; Meaningfully improves customer outcomes
Industry & Context.
Work on some of the hardest problems in applied AI; Figuring things out as you go
What They're Looking For.
Must Have
5+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up, Python, JavaScript and systems fundamentals, Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling, Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations, Can explain technical tradeoffs clearly and build trust with developer audiences, Take responsibility for outcomes, not just recommendations, Have a bias toward action and enjoy figuring things out as you go, Are excited about operating AI agents in production, not just building demos
Nice to Have
You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks, Worked with LLM evaluation, observability, or guardrails, Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts, Have shipped and operated production software and are comfortable owning systems under real-world constraints
What You'll Do.
Co-architect and co-build production AI agents with customer engineering teams
Own the technical win in pre-sales by designing POCs
answering deep technical questions
and guiding evaluations
Help customers deploy and operate agent-based applications such as conversational agents
and multi-step workflows
Advise customers post-sale on architecture
and roadmap-level decisions
and workshops for developer audiences
Surface field feedback and contribute reusable patterns
and example code that scale across customers
Occasionally contribute code upstream when it meaningfully improves customer outcomes
How You'll Work.
Team & Collaboration
Partner closely with customer engineers across the full lifecycle; Co-architect and co-build production AI agents with customer engineering teams; Contribute reusable patterns, cookbooks, and example code that scale across customers; Work together
Communication Scope
Explain technical tradeoffs clearly; Build trust with developer audiences; Run technical demos, trainings, and workshops for developer audiences
Full Job Description
ABOUT US 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. 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. Today, LangChain, LangGraph, LangSmith, and Fleet 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. ABOUT THE TEAM The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact i
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