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Описание вакансии
Текст:
TL;DR
Partner Engineer (AI): Building reference architectures, integration patterns, and technical enablement programs that help cloud providers and systems integrators deliver LangChain agentic AI solutions with an accent on partner engineering, agent development, and scalable technical assets. Focus on designing reusable integrations, building certification and workshop programs, evaluating agent behavior, and solving complex partner-led deployment challenges.
Location: San Francisco, CA; on-site
Annual salary: $170,000–$200,000 USD
Company
LangChain builds open-source frameworks and a platform for building, evaluating, deploying, and operating intelligent agents at scale.
What you will do
- Build reference architectures and integration patterns for cloud partner co-selling, marketplace listings, and joint solution briefs across GCP and Azure.
- Develop and run a services partner enablement program with certification tracks, workshops, delivery playbooks, and implementation guides based on the agent development lifecycle.
- Work with systems integrator centers of excellence to create repeatable solutions that partners can scope, build, and deploy independently.
- Support partner account teams with technical evangelism, solutioning, presentations, events, summits, and joint webinars.
- Maintain joint technical roadmaps with strategic services partners and help grow technical champions into partner centers of excellence.
- Serve as a technical escalation point and route partner and field feedback to product and engineering.
Requirements
- 7+ years of experience in a technical, partner-facing, or customer-facing role such as Partner Engineer, Solutions Architect, or Sales Engineer.
- Experience partnering with systems integrators, cloud providers, technology partners, or ISVs on complex technical solutions from design through delivery.
- Experience creating enablement programs, certifications, workshops, delivery playbooks, sample repositories, or reusable reference architectures.
- Hands-on experience with LLM frameworks such as LangChain or LangGraph, RAG patterns, agent architecture, evaluation frameworks, prompts, and agent behavior.
- Strong Python skills and working knowledge of GCP and/or Azure services, vector stores, tool integration, and API design.
- Strong technical presentation and communication skills, including communication with technical, business, and C-suite stakeholders.
Culture & Benefits
- Meaningful ownership and impact in a rapidly growing AI product company.
- Competitive compensation including base salary, variable compensation where relevant, equity, benefits, and perks.
- Medical, dental, and vision coverage.
- Flexible vacation and a 401(k) plan.
- Meals provided on US in-office days.
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