Job Overview
Job TitleApplied AI Engineer Life Sciences
Job TypeFull Time
Offered Salary$320,000
LocationNew York, NY
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Job Description
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 team, focused on maximizing 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. That means making Claude the go-to tool for the life sciences ecosystem from early discovery in academia to paradigm shifting biotech to reimaging pharma pipelines — and building the technical infrastructure to back that up. 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. This role will be part of the founding Beneficial Deployments applied AI team focused on bringing more of life sciences closer to the frontier and be responsible for building with our partners.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
- 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 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.
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 prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application processKey skills/competency
- Applied AI Engineering
- Life Sciences AI
- LLM Development
- Scientific Computing
- Biomedical Research
- Production Systems
- Agent Architectures
- Data Strategy
- Research Partnerships
- Technical Leadership
How to Get Hired at Anthropic
- Tailor your resume: Highlight experience in software engineering, life sciences research, and LLM development. Quantify achievements.
- Showcase LLM expertise: Detail projects involving prompting, agent architectures, and evaluation frameworks.
- Emphasize partnership skills: Demonstrate experience collaborating with external teams and understanding complex workflows.
- Address the scrappy mentality: Provide examples of building from scratch and driving clarity in ambiguity.
- Prepare for technical and behavioral interviews: Be ready to discuss your experience in life sciences and AI, as well as your problem-solving approach.
Frequently Asked Questions
Find answers to common questions about this job opportunity
01What kind of technical skills are most important for the Applied AI Engineer, Life Sciences role at Anthropic?
02How does Anthropic ensure AI is used beneficially in the life sciences sector?
03What is the expected hybrid work policy for the Applied AI Engineer, Life Sciences position at Anthropic?
04Can Anthropic sponsor visas for international candidates for the Applied AI Engineer, Life Sciences role?
05What is Anthropic's approach to AI research and development in the life sciences?
06What kind of partners will an Applied AI Engineer at Anthropic work with in life sciences?
07How does Anthropic encourage diversity and inclusion in its AI development efforts?
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