Applied AI Architect, Partnerships

As an Applied AI Architect on the Partnerships team at Anthropic, you will be a pre-sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP).

You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.

Responsibilities:

• Strategic Technical Partnership: Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities.
• Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment.
• Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance.
• Partner Ecosystem & Events: Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences.

You may be a good fit if you have:

• 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager.
• Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery.
• Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders.
• Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders.
• Experience designing scalable cloud architectures and integrating with enterprise systems.
• Familiarity with common LLM frameworks and tools or a background in machine learning or data science.