Anthropic, a public benefit corporation headquartered in San Francisco, is seeking an Applied AI Engineer for its Beneficial Deployments Life Sciences team in London, UK. The role involves partnering with nonprofits, research institutes, academic medical centres and public‑sector funders to deploy Claude in clinical trials and drug repurposing, helping design better trials, flag risks, build tools for evidence generation, and create reusable infrastructure to accelerate therapeutic development for rare and neglected diseases.
Applied AI Engineer, Beneficial Deployments (Life Sciences - Clinical Trials/Drug Repurposing) en Anthropic
Híbrido - London, UK
Más vacantes en AnthropicSalary
GBP 225,000 - 255,000
Requirements
Skills
- Hands‑on experience designing, running or analysing clinical trials, or finding new uses for existing medicines
- Deep experience in one of the above; both is a bonus
- Experience contributing 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: 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
- Scrappy mentality: comfortable in ambiguity, wear several hats, and get results for partners
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
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
Technologies
LLMMCP serversAgent skillsBenchmarks
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