Applied AI Engineer, Beneficial Deployments (Life Sciences - Clinical Trials/Drug Repurposing)

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 Beneficial Deployments 

Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences - focusing on raising the floor for those who need it most.

About the Role

We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team. This is a partner-facing role: you'll support nonprofits, research institutes, academic medical centres and public-sector funders as they use Claude to get treatments to patients with rare and neglected diseases, where there is little or no commercial incentive to fund development.

The role focuses on two areas where we think Claude can help these partners today. The first is clinical trials. Trials in these diseases have small patient populations, investigator-led or nonprofit funding and little operational support, and they often stall on protocol quality, operational risk and site start-up. Claude can help teams design better trials and start them sooner. The second is drug repurposing: finding new uses for approved, usually off-patent or generic medicines, whose known safety profiles can let a good hypothesis reach patients years sooner than a new molecule.

You'll advise and embed in partners' teams, building alongside their engineers, scientists and clinicians.

Responsibilities

• Work with partners' trial teams to design, review and prioritise clinical trials with Claude: drafting and reviewing protocols and statistical analysis plans, and flagging enrolment and operational risks.
• Build and validate tools that help partners find new uses for approved, mostly off-patent medicines in rare and neglected diseases, from literature, omics and patient data, and assemble the evidence so the partner can decide the next step.
• Build reusable infrastructure other institutions can adopt (MCP servers for biomedical data sources, agent skills, benchmarks grounded in real clinical questions), and feed what you learn in the field back to product, engineering and research.

You Might Be a Good Fit If You Have

• Hands-on experience designing, running or analysing clinical trials, or finding new uses for existing medicines. Deep experience in one; both are a bonus. Having contributed to a regulatory submission for a trial is a plus.
• Comfort with biomedical data: literature, omics, and real-world patient data (health records, registries, claims), ideally inside secure or trusted research environments.
• Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure it.
• Experience working directly with external partners or customers in a technical role.
• Clear written and verbal communication: docs other institutes can use without you, and results clinicians trust.
• A scrappy mentality: you're comfortable in ambiguity, wear several hats, and do what it takes to get a result for a partner.