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 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.

The annual compensation range for this role is listed below.

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:

£225,000—£255,000 GBP

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 as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you ----- addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on pri