Join LangChain as a Partner Engineer to build technical foundations for partner ecosystems in AI agent development.
Posted by employer 1 month ago
First seen on Joblaze 1 month ago
Last verified on the company career page 11 hours ago
Requirements
Not disclosed in this posting: work arrangement, visa sponsorship.
Benefits
Joblaze summary
In the Partner Engineer role at LangChain, the individual is responsible for developing reference architectures and integration patterns that facilitate technical collaboration with cloud providers and systems integrators. Key skills include experience with LLM frameworks, strong Python proficiency, and the ability to create enablement programs that empower partners to operate independently. This position is ideal for seasoned professionals with a background in technical partner engagement, particularly those who can navigate both engineering and business discussions effectively.
Joblaze insights
Quick facts
From the original posting
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
San Francisco
$185K to $225K
Standard company text repeated across LangChain's postings is omitted here.