About the job
Join Our Mission at LangChain
At LangChain, we are dedicated to making intelligent agents a standard part of everyday life. Our goal is to provide developers with the essential tools to transition from prototyping to deploying production-ready AI agents that can be trusted by teams. Starting as a widely embraced open-source initiative, we have evolved to offer a robust platform for constructing, assessing, deploying, and managing agents on a large scale.
Our suite of products, including LangChain, LangGraph, LangSmith, and Agent Builder, empowers teams to deliver real AI solutions across various sectors, from startups to major corporations. Esteemed clients such as Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500 rely on LangChain to enhance their AI capabilities.
Having successfully raised $125M in Series B funding from prominent investors such as IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we are in an exciting phase of growth where innovation thrives, and every team member's input significantly influences our progress and collaborative processes. At LangChain, your efforts will directly impact the application of AI technology in the real world.
About Our Deployed Engineering Team
The Deployed Engineering team plays a vital role in collaborating with organizations to design and implement AI agents in production. Our mission is to transform innovative concepts into reliable systems that teams can depend on.
This is a technical, hands-on team that collaborates closely with client engineers throughout the entire project lifecycle, from pre-sales assessments to post-deployment support. Our primary focus is on achieving technical success, co-designing agent architectures, and ensuring that clients can manage agents effectively at scale with the help of the LangChain suite.
Your Role as a Deployed Engineer
As a Deployed Engineer, you will tackle some of the most challenging issues in applied AI—focusing on delivering systems that teams actually depend on in production, rather than mere demonstrations or research projects. The feedback loop is rapid, the results are tangible, and your contributions will directly influence the construction of AI agents in practical applications.

