Deployed Engineer (Atlanta)

About LangChain

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, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement.

About the Role

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.

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, 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

Qualifications

Minimum Qualifications

• 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
• Experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
• Comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
• Can explain technical tradeoffs clearly and build trust with developer audiences
• Bias toward action with strong accountability for outcomes

Nice to Haves

• Deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
• Experience with LLM evaluation, observability, or guardrails
• Experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
• Experience shipping and operating production software under real-world constraints