Key skills
PythonJavaScriptSystems fundamentalsAgent-based applicationsLLM-powered applicationsMulti-step workflowsOrchestrationFailure handlingAI agent deploymentCloud environmentsContainersKubernetes conceptsProduction software operationBias toward actionGoAILLMLangChainLangGraphAWSAzureGCPKubernetesSales
About this role
LangChain is focused on making intelligent agents ubiquitous, providing tools for building and deploying AI agents. The Deployed Engineer will work on applied AI systems, collaborating with customer engineering teams to co-architect and build production AI agents, while also engaging in pre-sales activities and providing post-sale guidance.
Responsibilities:
- 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
Requirements:
- 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
- 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
- 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