About this role
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 an Applied AI Engineer on the Startups team at Anthropic, you will be a trusted technical advisor to the top AI-native life sciences and biotech startups as they grow from early product to scale. Some of these companies build products on Claude that they sell to the rest of the industry, and others do the science themselves and want Claude woven into how their own research runs, and this role works with both. You'll lead deep technical engagements, partnering directly with startup engineering and scientific teams to help them build their products on Claude and run their own research with it, advising on implementation and agent design as they build what is newly possible with AI in the life sciences. You will bridge the gap between what Claude can do and what the life sciences need, working alongside some of the strongest teams in the field on problems that matter and pushing the boundaries of AI in science as you go.
Working closely with Applied AI Architects, Account Executives, and Anthropic's Product, Engineering, and Research teams, you'll help startups build at the edge of what is possible with Claude. You'll leverage your AI engineering expertise and your scientific domain knowledge to develop custom evaluation frameworks, design scalable architectures, and create the technical resources that enable life sciences startups to succeed with Claude.
Responsibilities
• Serve as a deep technical advisor to high-potential life sciences and biotech startups, whether Claude sits inside the product they sell or inside the way they make discoveries, working alongside them to build innovative use cases that push the boundaries of AI in scientific research and development
• Work hands-on with startup engineering teams and their scientists through pair programming and architecture reviews that accelerate their development, and understand their scientific workflows end to end so that your guidance fits into real research pipelines
• Develop prototypes and technical documentation, including evaluation suites, scientifically grounded benchmarks, AI engineering techniques, and architecture diagrams, that enable startups to build, operate, and scale with Claude
• Create reference implementations and sample code that many companies can adopt without starting from scratch, such as example MCP servers for domain-specific data sources like genomics platforms, literature databases, and experimental repositories, along with agent skills for common scientific workflows
• Collaborate closely with Applied AI Architects to maintain context and continuity across customer engagements
• Identify patter