Langchain Deployed Engineer at LangChain works with customers to co-architect and build production AI agents. The role includes owning the technical win in pre-sales and advising customers post-sale on architecture and best practices.
Responsibilities
You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world.
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, research agents, and multi-step workflows
Advise customers post-sale on architecture, best practices, and roadmap-level decisions
Run technical demos, trainings, and workshops for developer audiences
Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
Occasionally contribute code upstream when it meaningfully improves customer outcomes
This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement
What You’ll Bring
3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
Strong Python, JavaScript and systems fundamentals
Qualification
You’ve deployed AI agents in productionWorked with LLM evaluation
Preferred
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
