Partner Engineer
LangChain is hiring a Partner Engineer in San Francisco, United States. It pays $185k-$225k a year and Level rates it ; you can apply on LangChain.
Level's read on this job
- Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
- The posting mentions Gemini, LangGraph and Bedrock among its tools and skills.
- Level classes it as a senior role.
- LangChain has 103 other open roles on Level.
AI in this role
Build technical reference architectures and integration patterns for AI agent ecosystems with cloud hyperscalers.
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.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
How we rate this
Partner Engineer at LangChain rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Tell me about a project where partner integrations was part of your work. What did you do?
- Tell me about a project where cloud architecture was part of your work. What did you do?
- Walk me through how you've used Gemini in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, Partner Integrations, Cloud Architecture, and Gemini. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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