Applied AI Engineer, Startups (Life Sciences)

Anthropic•San Francisco, NY

3d•Hybrid

About The Position

Anthropic is hiring an Applied AI Engineer for its Startups team, focused on life sciences and biotech. The role serves as a trusted technical advisor to AI-native startups, helping them build products on Claude and integrate Claude into their own scientific research workflows. The engineer leads technical engagements with startup engineering and scientific teams, advising on implementation, agent design, evaluation, and architecture as companies develop AI-enabled life sciences applications and research processes. Working with Applied AI Architects, Account Executives, and Anthropic Product, Engineering, and Research teams, the role develops custom evaluation frameworks, scalable architectures, technical resources, prototypes, documentation, reference implementations, and sample code. The engineer identifies recurring challenges in deploying AI in the life sciences and shares insights with internal teams to inform model capabilities and product features. The role also creates technical content, represents Anthropic in the startup ecosystem, and travels to customer sites for workshops, implementation guidance, and relationship building. The position requires deep life sciences or biotech experience and at least four years of technical experience in a relevant engineering, research, or founder role. The listed annual salary range is $280,000–$320,000 USD. Anthropic currently expects staff to work from an office at least 25% of the time, though some roles may require more. A bachelor’s degree or an equivalent combination of education, training, and/or experience is the stated minimum education requirement.

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.
At least 4 years of technical experience as a software engineer, ML or research engineer, computational biologist, research scientist, or technical founder.
Either production experience building LLM-powered applications—including prompting, context engineering, agent architectures, evaluation frameworks, and deployment at scale—or a track record of applying AI to real scientific work in a lab or research setting.
Experience with startups or high-growth companies and an interest in working with founders and fast-moving small teams.
Strong technical communication skills, including translating complex AI concepts into architectural decisions and implementation plans for engineering and scientific audiences.
Ability to run technical workshops, hackathons, or developer-focused events.
Collaborative approach, ability to context-switch across scientific domains and use cases, and commitment to making powerful technology safe and beneficial.
Bachelor’s degree or equivalent combination of education, training, and/or experience.
Education or experience in a field relevant to the role.

Responsibilities

Serve as a deep technical advisor to life sciences and biotech startups building Claude-powered products or using Claude in their scientific discovery workflows.
Work hands-on with startup engineering teams and scientists through pair programming and architecture reviews, and understand their scientific workflows end to end.
Develop prototypes and technical documentation, including evaluation suites, scientifically grounded benchmarks, AI engineering techniques, and architecture diagrams.
Create reference implementations and sample code, such as MCP servers for scientific data sources and agent skills for common scientific workflows.
Collaborate with Applied AI Architects to maintain context and continuity across customer engagements.
Identify patterns and challenges across engagements and share insights with Product, Engineering, Research, and the broader Applied AI team, including feedback on model capabilities and product features.
Create technical content for startup audiences, including documentation, tutorials, and sample code.
Represent Anthropic in the life sciences startup ecosystem through community activities such as hackathons, webinars, technical office hours, founder events, and research show-and-tells.
Travel to customer sites for workshops, implementation guidance, and relationship building.