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Technical Program Manager, Inference Performance

Anthropic - San Francisco, CA | Seattle, WA

Posted Feb 3, 2026

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About this role

Technical Program Manager, Inference Performance San Francisco, CA | Seattle, WA About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role As a Technical Program Manager for Inference, you'll be the critical bridge between our inference systems and the broader organization. You'll drive strategic initiatives across inference runtime and accelerator performance-coordinating model launches, managing cross-platform dependencies, and ensuring reliability across multiple hardware targets. This role is essential for keeping our most contended infrastructure teams shipping effectively while Research, Product, and Safety all depend on their output. Responsibilities: - Systems Integration & Coordination : Lead cross-functional initiatives for new infrastructure integration, establishing clear ownership, timelines, and communication channels between teams. Drive end-to-end planning for major infrastructure transitions including platform modernization and new tech adoption. - Performance & Efficiency: Partner with engineering teams to identify optimization opportunities, track performance metrics, and prioritize work that unlocks capacity gains. Coordinate across runtime and accelerator layers to ensure efficiency wins ship without compromising reliability. - Launch Coordination: Drive end-to-end readiness for model and feature launches across multiple hardware platforms. Establish processes for cross-platform validation, manage launch timelines, and ensure smooth handoffs between runtime, accelerator, and downstream teams. - Strategic Planning: Own and prioritize the inference deployment roadmap, working closely

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