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Applied AI Architect, Beneficial Deployments (Life Sciences)

Anthropic · London, UK

Location
London, UK
Funding
$15.3B
Posted
Sep 9, 2026

Anthropic is hiring a Applied AI Architect, Beneficial Deployments (Life Sciences) based in London, UK. Every apply link on Engg.space goes straight to the company's own careers page - no recruiter middleman, no generic job-board form.

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Role details

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. About the Role We're looking for an Applied AI Architect to join Beneficial Deployments, 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 reimagining pharma pipelines. This role combines technical expertise with deep relationship-building. You'll be the primary technical advisor for our life sciences partners, including flagship research institutions like The Howard Hughes Medical Institute (HHMI) and The Allen Institute. You'll drive engagements from discovery through deployment, working closely with the life sciences segment lead and Applied AI Engineers to deliver impact. This role will be part of the founding Beneficial Deployments Applied AI team focused on bringing life sciences closer to the frontier. Responsibilities 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. You Might Be a Good Fit If You Have 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 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: £165,000 - £190,000 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 buildin

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