You'll work directly with flagship research partners like Howard Hughes Medical Institute and The Allen Institute, embedded in their scientific workflows. This isn't consulting from the outside , you'll be building alongside their engineers, prototyping agents that fit into real research pipelines, and developing the ecosystem-level tooling (MCP servers, benchmarks, reusable agent skills) that extends Claude's usefulness across the broader life sciences community.

Responsibilities:

Partner deeply with flagship life sciences research institutions , understand their scientific workflows end-to-end, build hands-on with their engineering teams, and help take projects from early exploration to production systems integrated into how they do science day-to-day.

Develop reusable ecosystem infrastructure, like MCP servers for domain-specific data sources (genomics platforms, literature databases, experimental repositories), instruments, scientifically-grounded benchmarks, and agent skills that other institutions can adopt without starting from scratch.

Identify what's actually hard about deploying AI in life sciences (heterogeneous data, auditability requirements, the prototype-to-trust gap) and feed those findings back to product, engineering, and research.

Create technical content and documentation that lets partners self-serve, so what works for one institution can scale globally without the same level of hand-holding.

You might be a good fit if you have:

4+ years as a Software Engineer, Forward Deployed Engineer, or technical founder , with production experience shipping systems that real users depend on.

Deep research experience in life sciences, biomedical research, or scientific computing. Bonus if you've studied genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.

Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.

Builder credibility from shipping production code as a software engineer, forward-deployed engineer, or technical founder.

A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.

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We're looking for an Applied AI Engineer to join our Beneficial Deployments team, focused on maximising the impact of Claude in the life sciences. Our goal is ambitious: accelerate scientific progress from R&D through translation by an order of magnitude.

You'll work directly with flagship research partners like Howard Hughes Medical Institute and The Allen Institute, embedded in their scientific workflows. This isn't consulting from the outside — you'll be building alongside their engineers, prototyping agents that fit into real research pipelines, and developing the ecosystem-level tooling (MCP servers, benchmarks, reusable agent skills) that extends Claude's usefulness across the broader life sciences community.

Responsibilities:

• Partner deeply with flagship life sciences research institutions — understand their scientific workflows end-to-end, build hands-on with their engineering teams, and help take projects from early exploration to production systems integrated into how they do science day-to-day.
• Develop reusable ecosystem infrastructure, like MCP servers for domain-specific data sources (genomics platforms, literature databases, experimental repositories), instruments, scientifically-grounded benchmarks, and agent skills that other institutions can adopt without starting from scratch.
• Identify what's actually hard about deploying AI in life sciences (heterogeneous data, auditability requirements, the prototype-to-trust gap) and feed those findings back to product, engineering, and research.
• Create technical content and documentation that lets partners self-serve, so what works for one institution can scale globally without the same level of hand-holding.

You Might Be a Good Fit If You Have:

• 4+ years as a Software Engineer, Forward Deployed Engineer, or technical founder — with production experience shipping systems that real users depend on.
• Deep research experience in life sciences, biomedical research, or scientific computing. Bonus if you've studied genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.
• Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.
• Builder credibility from shipping production code as a software engineer, forward-deployed engineer, or technical founder.
• A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.

Logistics:

• Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

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