About the job
About LangChain:
At LangChain, we are dedicated to revolutionizing the role of intelligent agents in everyday applications. Our goal is to provide developers with the tools needed to transition from initial prototypes to robust, production-ready AI agents that businesses can trust. Initially established as widely embraced open-source solutions, we have expanded to deliver a comprehensive platform that facilitates the building, assessment, deployment, and management of AI agents on a large scale.
Our innovative products, including LangChain, LangGraph, LangSmith, and Agent Builder, empower teams at both startups and Fortune 500 companies to launch impactful AI solutions. Renowned organizations such as Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500 rely on LangChain for their AI initiatives.
With a solid backing of $125M from top-tier investors including IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we are poised for accelerated growth as we continue to innovate and enhance our offerings. At LangChain, your work will directly influence the evolution of AI technology in practical applications.
Role Overview
We are seeking an experienced Solutions Architect to join our Professional Services team. In this role, you will collaborate closely with enterprise clients to architect, implement, and optimize high-performance AI infrastructure and agent systems. You will take the lead in designing scalable and secure infrastructure deployments and creating reliable, well-evaluated agent applications that address real-world business challenges.
This position merges software development, infrastructure engineering, and client-facing skills, requiring proficiency in areas ranging from Kubernetes cluster design to multi-agent system architecture. You will need to exhibit deep technical expertise in both infrastructure development and agent engineering.
This is an opportunity to make a significant impact on client success, influence best practices, and engage with groundbreaking AI technology within a supportive team environment that promotes engineering excellence.
Key Responsibilities:
Infrastructure & Platform Development: Create scalable, highly available infrastructure for AI platform deployments, focusing on compute, storage, networking, security, enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines.
Agent Development & Engineering: Architect multi-agent systems using various approaches, implement agent logic utilizing modern frameworks (LangChain/LangGraph), and establish comprehensive evaluation frameworks for agent performance.

