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Salary: USD 240,000 - 315,000 / annual
Anthropic is seeking an Applied AI Architect to serve as a pre-sales technical advisor for enterprise customers adopting Claude. You will combine deep technical expertise with customer-facing skills to architect innovative LLM solutions addressing complex business challenges while maintaining high standards for safety and reliability.
You will partner with account executives and sales teams to understand customer requirements and translate them into technical solutions, ensuring alignment between business objectives and implementation. You'll serve as the primary technical advisor throughout the Claude adoption journey—from discovery and evaluation through deployment—coordinating internally across multiple teams to drive customer success.
Key responsibilities include supporting customers building with both the Claude API and Claude for Work; creating and delivering compelling technical content tailored to different audiences (from engineering deep dives to executive business-value conversations); guiding technical architecture decisions and integration into existing technology stacks; helping customers develop evaluation frameworks to measure Claude's performance for their use cases; identifying common integration patterns and contributing insights back to Product and Engineering teams; occasional travel to customer sites for workshops and relationship building; and maintaining strong knowledge of the latest LLM capabilities and implementation patterns.
You should have 5+ years in technical customer-facing roles such as Solutions Architect, Sales Engineer, or Technical Account Manager, with experience navigating complex enterprise buying cycles involving multiple stakeholders. You'll need exceptional ability to build relationships and communicate technical concepts to diverse audiences (C-suite executives, engineering teams, IT leadership). Strong technical communication skills, experience designing scalable cloud architectures and integrating with enterprise systems, comfort with Python, and familiarity with common LLM frameworks or background in machine learning/data science are essential. The role requires 3 days in office per week.
