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. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

About the Role

Cloud providers and Systems Integrators help LangChain reach customers that our direct sales and customer engineering teams can't reach on their own. This role is the technical foundation behind that ecosystem.

You'll build the reference architectures, integration patterns, and enablement programs that make partner motions work technically: co-sell with cloud hyperscalers, and independent delivery capability at systems integrators and global systems integrators (GSIs). You build with and for a partner, whose technical team then takes what you built to dozens of their own clients.

About the role

AWS, Google Cloud, and Microsoft Azure help LangChain reach customers that our direct sales and customer engineering teams can't reach on their own. This role is the technical foundation behind those cloud alliances.

You'll build the reference architectures, integration patterns, and co-sell assets that make our cloud motions work technically. That covers marketplace listings and private offers, joint solutions with cloud field teams, and technical wins on named accounts. You build with and for each cloud provider, and their partner and field teams then take what you built to many of their own customers. When a cloud deal involves a services partner, you make sure that partner can deliver on LangChain.

Key responsibilities

Cloud partner engineering (AWS, GCP, Azure)

Own the technical relationship with partner and field teams at AWS, Google Cloud, and Microsoft Azure

Build reference architectures and integration patterns for running LangChain, LangGraph, DeepAgents and LangSmith on each cloud, including integrations with each provider's native AI and data services (for example Amazon Bedrock, Gemini Enterprise, AzureAI)

Support the technical side of co-sell: joint solution briefs, deployment guides, and validated architectures that cloud sellers can bring to their customers

Partner with cloud account teams on solutioning for named accounts, from discovery through technical win

Keep our marketplace listings, deployment options, and co-sell technical assets current as the product evolves

Enable cloud field and partner teams through workshops, demos, and technical briefings so they can position LangChain without pulling in our engineers for every deal

Build and maintain joint technical plans with each cloud provider, turning shared account and industry priorities into a concrete set of reference assets

Marketplace motions with services partners

Support systems integrators and resellers when they're part of a cloud deal, such as marketplace private offers transacted through a channel partner or joint deployments on a customer's cloud

Give those partners the technical assets they need to scope and deliver LangChain on AWS, GCP, or Azure, using existing reference architectures and implementation guides rather than a standalone enablement program