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

Partner technical evangelism and feedback

• Serve as a technical escalation point for complex deployments sourced through cloud partners

• Represent LangChain at cloud provider events, summits, and joint webinars

• Gather feedback from cloud partners and the field, and route it back to product and engineering

What we're looking for

7+ years of experience in a technical, partner-facing or customer-facing role such as Partner Engineer, Partner Solutions Architect, Solutions Architect, or Sales Engineer. Experience at or alongside a hyperscaler is a strong plus. We also like former founders and technical leaders, so if you have an unusual background but the right skill set, you're welcome to apply.

Cloud and partner experience

• Track record of working with AWS, Google Cloud, or Microsoft Azure partner and field teams to drive co-sell, from joint solution design through technical win

• Familiarity with cloud marketplace mechanics such as listings, private offers, and channel partner offers, and with hyperscaler co-sell programs

• Experience enabling a partner's field or technical teams so they can position and deploy a product without depending on you for every deal

• Comfortable working across engineering, partnerships, and sales at the same time

• Strong presentation and technical communication skills, able to translate between technical and business stakeholders, including C-suite executives

Agent engineering and development

• Hands-on experience building with LLM frameworks such as langchain, langgraph, or similar, including RAG patterns and agent architecture

• Experience designing evaluation frameworks and iterating on prompts and agent behavior based on results

• Strong Python skills

Cloud architecture and integration

• Deep working knowledge of at least one of AWS, GCP, or Azure, and familiarity with the other two. Strong background in GCP or Azure preferred.

• Hands-on experience with cloud AI platforms and managed model services

• Experience designing integrations, sample repositories, or reference architectures that other teams can pick up and reuse

• Familiarity with vector stores, tool integration, and API design in agentic systems

Key attributes

• You build credibility with a cloud provider's technical and field teams and act as their trusted advisor on LangChain

• Building and evangelizing are both part of the job. You're equally comfortable writing an integration and presenting it at a cloud summit

• You build assets that scale. A reference architecture should work across every cloud account team, not only the one in front of you

• You're comfortable with variety. AWS, GCP, and Azure each have their own programs, sellers, and ways of working, and switching between them doesn't throw you off

Location:

San Francisco

Compensation:

$185K to $225K

Compensation Philosophy:

We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.

Benefits

Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.