2 months ago
Responsibilities
- Co-architect and co-build production AI agents with customer engineering teams.
- Own the technical win in pre-sales by designing proofs of concept, answering technical questions, and guiding evaluations.
- Help customers deploy and operate 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.
- Occasionally contribute code upstream when it improves customer outcomes.
- Travel 40% to customer sites for deployment, onboarding, and ongoing technical engagement.
Requirements
- 3+ years of experience in a relevant technical role such as software engineering, customer engineering, solutions engineering, founding engineering, or product engineering.
- Strong Python, JavaScript, and systems fundamentals.
- Experience designing agent-based or LLM-powered applications with multi-step workflows, orchestration, and failure handling.
- Comfort working directly with customers during proofs of concept, architecture reviews, and technical evaluations.
- Ability to explain technical tradeoffs clearly and build trust with developer audiences.
- Experience deploying AI agents in production, particularly with LangChain, LangGraph, or similar frameworks, is preferred.
- Experience with LLM evaluation, observability, or guardrails is preferred.
- Experience with AWS, GCP, Azure, containers, and basic Kubernetes concepts is preferred.
- Experience shipping and operating production software under real-world constraints is preferred.
Benefits
- Medical, dental, and vision coverage
- Flexible vacation
- 401(k) plan
- Meals on in-office days in the US
- 40% travel to customer sites is required
Categories
Forward DeployedSolutions Engineering
About LangChain
LangChain builds open-source frameworks and a commercial platform for developing, evaluating, deploying, and operating LLM-powered agents and applications. Its LangSmith suite provides observability, testing, deployment, and governance for enterprise AI workloads; customers include Nvidia, LinkedIn, Workday, and Bridgewater. Privately held and headquartered in San Francisco, the company was founded in 2022.