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Salary: USD 150,000 - 250,000 / annual
LangChain is hiring a Deployed Engineer to work directly with enterprise customers building and operating AI agents in production. This is a hands-on technical role at the intersection of engineering, product, and go-to-market, focused on turning prototypes into reliable production systems.
You'll co-architect and co-build production AI agents with customer engineering teams, owning the technical win from pre-sales POC design through post-deployment advisory. Responsibilities include designing and evaluating agent architectures, helping customers deploy and operate agent-based applications (conversational agents, research agents, multi-step workflows), advising on best practices and roadmap decisions, and running technical demos and workshops for developer audiences.
The role requires deep technical collaboration with customers during evaluations and architecture reviews. You'll surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across the customer base. Occasionally you'll contribute code upstream when it meaningfully improves customer outcomes. Travel to customer sites is expected up to 40% of the time.
You bring 6+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, or founding/product engineering), ideally in a startup or scale-up environment. Strong Python and JavaScript skills with solid systems fundamentals are essential. You've designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling. You're comfortable working directly with customers, can explain technical tradeoffs clearly, and build trust with developer audiences. You take responsibility for outcomes, have a bias toward action, and are excited about operating AI agents in production rather than building demos.
Nice-to-haves include production AI agent deployment experience (especially with LangChain, LangGraph, or similar frameworks), work with LLM evaluation, observability, or guardrails, cloud environment experience (AWS, GCP, Azure), containers, and Kubernetes concepts.
About LangChain
AI / Data / Infrastructure — developer platform and framework for building LLM applications and agents.
