
Job Overview
Location
Phoenix, AZ
Job Type
Full-time
Category
Software Engineering
Date Posted
April 22, 2026
Full Job Description
đź“‹ Description
- • As a Deployed Engineer at LangChain, you will work on some of the hardest problems in applied AI — building production-ready AI agents that real teams depend on, not just demos or research. Your work will directly shape how AI agents are built and operated in the real world, with fast feedback loops and visible impact.
- • Day to day, you will co-architect and co-build production AI agents with customer engineering teams, own technical wins in pre-sales by designing POCs and answering deep technical questions, help customers deploy and operate agent-based applications (conversational, research, multi-step workflows), advise post-sale on architecture and best practices, run technical demos and trainings, surface field feedback to create reusable patterns and cookbooks, and occasionally contribute code upstream when it improves customer outcomes.
- • LangChain is a fast-growing AI infrastructure company backed by $125M in Series B funding from top-tier investors including IVP, Sequoia, and Benchmark. Our tools — LangChain, LangGraph, LangSmith, and Fleet — are used by developers at companies like Replit, Coinbase, Workday, Lyft, Cloudflare, and 35% of the Fortune 500 to ship real AI products. We are a place where your contributions shape how AI technology shows up in the real world.
- • In this role, you will deepen your expertise in applied AI systems, gain hands-on experience deploying LLM-powered applications at scale, strengthen your customer-facing technical skills, and learn how to translate real-world feedback into scalable engineering patterns — all while making a tangible impact on how enterprises adopt AI agents.
Skills & Technologies
About LangChain, Inc.
LangChain, Inc. provides open-source software libraries and cloud services for building applications that integrate large language models with external data sources and workflows. Its tools help developers create retrieval-augmented generation systems, manage prompts, chain model calls, and monitor performance in production environments. The company was founded in 2023 and is headquartered in San Francisco, California.
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