Applied AI Engineer, Startups (Life Sciences)

Build Claude-based solutions with life sciences and biotech startups, helping move from prototypes to trusted scientific workflows.

Responsibilities

• Act as a deep technical advisor to life sciences and biotech startups, supporting use cases where Claude is embedded in the product or applied to how discoveries are made
• Work hands-on with startup engineering teams and scientists using pair programming and architecture reviews
• Map scientific workflows end to end so guidance aligns with real research pipelines
• Develop prototypes and technical documentation, including evaluation suites, scientifically grounded benchmarks, AI engineering techniques, and architecture diagrams
• Create reference implementations and sample code to help teams adopt solutions without starting from scratch, including example MCP servers for domain sources (genomics platforms, literature databases, experimental repositories) and agent skills for common scientific workflows
• Partner with Applied AI Architects to maintain context and continuity across customer engagements
• Spot recurring deployment challenges in life sciences, such as heterogeneous data, auditability requirements, and the gap between a working prototype and what scientists trust
• Share insights across Product, Engineering, Research, and the broader Applied AI team, including feedback on model capabilities and product features that accelerate discovery work
• Produce technical content for startup audiences, including documentation, tutorials, and sample code
• Represent Anthropic in the life sciences startup ecosystem through hackathons, webinars, technical office hours, in-person founder events, and research show-and-tells
• Travel to customer sites for workshops, implementation guidance, and relationship building

Requirements

• Deep experience in life sciences or biotech through research or industry work in areas such as genomics, drug discovery, molecular design, lab automation, or clinical development
• Strong personal perspective on bridging what AI can do today with what life sciences teams need
• 4+ years of technical experience as a software engineer, ML or research engineer, computational biologist, research scientist, or technical founder
• Production experience building LLM-powered applications, including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale, or a proven track record applying AI to real scientific work in labs or research settings
• Experience with startups or high-growth companies, with an interest in working with founders and small teams that move quickly
• Strong technical communication skills for translating AI concepts into architectural decisions and actionable implementation plans for both engineering and scientific audiences
• Ability to run technical workshops, hackathons, or developer-focused events
• Collaborative working style across teams, comfort context-switching across scientific domains and use cases, and a commitment to making powerful technology safe and beneficial

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space for collaboration

Location and Salary

• Location: San Francisco, CA (hybrid)
• Annual salary: USD 280,000 - 320,000

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role, demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years required correlate with internal job level requirements
• Hybrid policy: Expect staff to be in one of the offices at least 25% of the time; some roles may require more
• Visa sponsorship: Visa sponsorship is available, and if an offer is made, reasonable efforts will be made to support immigration with an immigration lawyer