L

LangChain

Builds open-source tools for making AI agents

Partner Engineer

Pre-Sales Solution EngineeringUpdated on Nov 12
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • At least 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.
  • A 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.
  • Ability to work across engineering, partnerships, and sales concurrently.
  • Strong presentation and technical communication skills, including the ability to translate between technical and business stakeholders, including C-suite executives.
  • 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.
  • Deep working knowledge of at least one of AWS, GCP, or Azure, and familiarity with the other two.
  • Hands-on experience with cloud AI platforms and managed model services.
  • Experience designing integrations, sample repositories, or reference architectures that other teams can reuse.
  • Familiarity with vector stores, tool integration, and API design in agentic systems.

Responsibilities

  • 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, such as Amazon Bedrock, Gemini Enterprise, and Azure AI.
  • Support the technical side of co-sell by creating 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 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 needing an engineer for every deal.
  • Build and maintain joint technical plans with each cloud provider, turning shared account and industry priorities into reference assets.
  • Support systems integrators and resellers when they are part of a cloud deal, including marketplace private offers transacted through a channel partner or joint deployments on a customer's cloud.
  • Provide partners with technical assets to scope and deliver LangChain on AWS, GCP, or Azure, using existing reference architectures and implementation guides.
  • 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 to product and engineering.

Desired Qualifications

  • Experience at or alongside a hyperscaler is a strong plus.
  • A background as a founder or technical leader is welcomed.
  • Strong background in GCP or Azure is preferred.

About the Company

LangChain

Builds open-source tools for making AI agents

LangChain makes free, open-source code libraries and a paid platform that software teams use to build and run AI agents, programs that use large language models to plan and finish tasks on their own. Its first library came out in October 2022, a month before ChatGPT, and in 2023 GitHub listed it among the open-source projects with the most contributors. Developers write agents with its LangChain, LangGraph, and Deep Agents libraries, which connect AI models to company data and software tools. Companies then pay for LangSmith, a platform that records each step an agent takes, scores its answers, and hosts finished agents. LangChain was founded in 2023 and is based in San Francisco.

Company size
201-500
Company stage
Late Stage VC
Total funding
$460M
Headquarters
San Francisco, CA
Founded
2023

Recently Posted Jobs

Explore more opportunities at LangChain

See more jobs