Deployed Engineer (Bay Area)

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. Today, our platform includes LangSmith, our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine.

About the Team

This hands-on, highly technical team works directly with companies building and running AI agents in production. Sales Engineers sit at the intersection of engineering, product, and go-to-market, partnering closely with customer engineers across the full lifecycle—from pre-sales evaluations to post-deployment advisory work—to achieve technical wins and operate agents reliably at scale.

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.
• Travel up to 40% 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.
• Experience designing agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling.
• Comfort working directly with customers during POCs, architecture reviews, and technical evaluations.
• Ability to explain technical tradeoffs clearly and build trust with developer audiences.
• Ownership mentality, bias toward action, and enthusiasm for operating AI agents in production.

Nice to Have

• Production deployment of AI agents, 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.
• Track record of shipping and operating production software under real-world constraints.