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Anthropic is hiring a Product Manager for Claude Science, an AI workbench designed to accelerate scientific research across biology, chemistry, physics, and related fields. Claude Science integrates literature search, specialized databases, scientific computing, analysis tools, and publication-ready outputs into a single environment—replacing dozens of disconnected tools researchers currently use.
In this role, you will own a major area of the Claude Science roadmap end-to-end. Responsibilities include: defining vision, strategy, and execution for a major product area while contributing to overall direction in a nascent category; spending meaningful time with working scientists in academic labs, biotech, pharma R&D, and research institutes to understand real workflows from hypothesis through publication; partnering with research teams to improve Claude's scientific capabilities, including defining target behaviors, building evals grounded in real workflows, and surfacing failure modes; driving model and feature launches end-to-end, coordinating across research, engineering, design, and go-to-market teams; identifying which scientific domains, data sources, tools, and integrations should be prioritized next; prototyping ideas with Claude to validate before committing engineering resources; ensuring responsible deployment of powerful capabilities through collaboration with safeguards, policy, security, and go-to-market partners; driving enterprise readiness including security reviews, compliance, admin controls, and procurement alignment for pharma and biotech adoption; ruthlessly prioritizing across scientific domains, customer segments, and workflows; defining success metrics specific to AI research products (adoption, retention, time-to-result, output trust); and maintaining current knowledge of the AI-for-science ecosystem, competitive landscape, and Claude Science's position within it.
You should have product management experience shipping technical products in close partnership with engineering and design, or equivalent experience as a founder, engineer, or scientist driving product direction. A scientific or deeply technical background is essential—you must be able to reason with domain experts about their workflows and diagnose where and why models fall short on scientific tasks. You need a strong grasp of AI and LLM concepts, daily use of AI tools, and comfort going deep on model behavior, prompting, and evaluation methodology. The ideal candidate thrives in ambiguity, uncovers non-obvious use cases for nascent capabilities, and brings those insights back to research teams.
