Applied AI Engineer, Beneficial Deployments (Life Sciences)
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What you'll do
- Serve as the primary technical advisor to life sciences research institutions and mission-driven organizations throughout their Claude adoption journey. Partner with the segment lead to understand scientific workflows end-to-end and translate them into impactful solutions from discovery through deployment.
- Transform partners into AI-native organizations through Claude Code and Claude Science enablements and research and business process evolution, so they can operate more effectively and build for where AI capabilities are headed.
- Design and lead cohort-based accelerators to scale our expertise and impact across multiple institutions at once.
- Identify what's actually hard about deploying AI in life sciences and feed those findings back to product, engineering, and research.
- Spot patterns across partners to inform what we build at the ecosystem level, including MCP servers for domain-specific data sources, scientifically grounded benchmarks and evals, and reusable agent skills.
- Create technical presentations, demos, and scalable content (documentation, tutorials, sample code) so what works for one institution can scale globally without the same level of hand-holding.
- Travel occasionally to partner sites for workshops, technical deep dives, and relationship building.
- Help shape team processes and culture as we scale from 1 to N.
What they're looking for
- 8+ years in a technical role, ideally with customer-facing exposure (Solutions Architect, Customer Engineer, Sales Engineer, Technical Account Manager, Product Engineer, Forward Deployed Engineer)
- Experience in life sciences, biomedical research, or scientific computing. Bonus if you've worked in genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.
- Experience working in or building trust with academic research institutions, biotech, pharma, or other mission-driven scientific organizations, and an understanding of their unique challenges and constraints
- Familiarity with common LLM implementation patterns, including prompt and context engineering, evaluation frameworks, agent architectures, and retrieval frameworks
- A love of teaching, mentoring, and helping others succeed
- A scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission
Nice to have
- Experience in life sciences, biomedical research, or scientific computing. Bonus if you've worked in genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
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 team, focused on maximizing the impact of Claude in the life sciences. Our goal is ambitious: accelerate scientific progress from R&D through translation. That means making Claude the go-to tool for the life sciences ecosystem from early discovery in academia to paradigm shifting biotech to reimagining pharma pipelines - and building the technical infrastructure to back that up.
You'll work directly with flagship research partners like The Howard Hughes Medical Institute (HHMI) 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 life sciences closer to the frontier.
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:
- 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.
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.
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 from @anthropic.com email 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 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 process.
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