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The Support Engineer provides technical support to enterprise customers, resolving complex issues and collaborating with internal teams to enhance product support. Responsibilities include account management, issue troubleshooting, and building customer relationships.

As a Technical Specialist at Anthropic, you'll engage with customers to foster adoption of their AI products, drive workshops, support pilots, and create technical content that enhances the customer experience with Claude Code and Cowork.

The Product Marketing Lead manages the go-to-market strategy for the Claude Platform, leading a team in product launches and sales enablement while collaborating on product development and marketing strategies.

The Strategic Deals Lead will drive execution of Anthropic's compute infrastructure strategy, manage partnerships, and support deal structuring while ensuring coordination across teams.

Lead the UI Platform team to enhance reliability, performance, and developer experience for Claude.ai's consumer products, while managing and growing the team and improving tooling and systems.

The Product Manager will drive enterprise API strategy, engage with developers, and lead product development to enhance multi-cloud integrations at Anthropic.

The Engineering Manager for Research Tools will lead a team of experts to optimize systems for AI research, support collaboration with various teams, and drive effective processes for system efficiency and team growth.

As a Product Manager for API Growth, you will drive growth for the Claude Platform through strategies targeting acquisition, activation, and monetization, while collaborating with cross-functional teams.

The Customer Success Programs Manager will lead programmatic customer success initiatives, focusing on AI-powered customer engagement and measure impact through data. Responsibilities include building programs, running live engagements, and collaborating across teams to enhance effectiveness and drive customer outcomes.

The ML Infrastructure Engineer will develop and scale AI safety systems infrastructure, optimize machine learning pipelines, and ensure reliable system performance while collaborating with research teams.