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Serve as technical lead for partnerships with cultural institutions and creative communities. Build demos, POCs, workshops, and documentation to help artists and institutions adopt Claude, Anthropic APIs, and related tools. Collaborate with product, research, and communications to grow usage and shape creative programs and strategy.

Research Scientist will develop methods for understanding LLMs, run experiments, analyze interpretability features, and communicate results. Collaborative team science is emphasized.

Oversee daily order management and provisioning for executed contracts, ensure billing matches contract terms, resolve cross-functional blockers, support month-end close and audits, document and improve quote-to-cash processes, test new product/system processes, and drive operational scaling projects.

As a Customer Success Manager, you will drive AI adoption, build strategic relationships, optimize customer usage of products, and manage customer experiences to maximize value.

The Strategic Account Executive manages relationships with AI company executives, leading negotiations, driving customer success, and aligning product strategies to business needs.

The Research Engineer for Interpretability will implement and analyze AI research experiments, optimize workflows, build supporting tools, and enhance model safety through mechanistic interpretability methods.

The Finance Systems Integration Engineer designs and builds integrations between ERP systems and financial applications, focusing on automation and data pipeline development while ensuring system reliability and data integrity.

The External Communications Manager will develop strategies to communicate Anthropic's AI research, build media relationships, and lead narrative efforts for research publications and milestones.

The role involves leading onboarding for sales teams, developing training programs, and ensuring effective enablement processes for AI-related products at Anthropic.

Lead and ship AI-native people products end-to-end: design and implement LLM-driven workflows, build full-stack features, engage internal HR stakeholders, make product and architecture decisions, and iterate rapidly on tools across the employee lifecycle.