We’re looking for an Applied AI Architect to join Beneficial Deployments, focused on maximizing the impact of Claude in the life sciences. The role combines technical expertise with deep relationship‑building, serving as the primary technical advisor to life sciences partners, leading engagements from discovery through deployment, and shaping product and research based on partner needs.
Applied AI Architect, Beneficial Deployments (Life Sciences) na Anthropic
Híbrido - London, UK
Ver mais vagas na AnthropicSalary
GBP 165,000 - 190,000
Requirements
Skills
- 8+ years in a technical role with customer-facing experience (e.g., Solutions Architect, Customer Engineer, Sales Engineer, Technical Account Manager, Product Engineer, Forward Deployed Engineer)
- Experience in life sciences, biomedical research, or scientific computing; bonus for work in genomics, neuroscience, or drug discovery
- Experience working with or building trust in academic research institutions, biotech, pharma, or other mission-driven scientific organizations
- Familiarity with common LLM implementation patterns, including prompt and context engineering, evaluation frameworks, agent architectures, and retrieval frameworks
- Love of teaching, mentoring, and helping others succeed
- Scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
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, 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 expertise and impact across multiple institutions simultaneously; identify hard problems in deploying AI in life sciences and feed findings back to product, engineering, and research
- Spot patterns across partners to inform ecosystem-level builds, including MCP servers for domain-specific data sources, scientifically grounded benchmarks and evaluations, and reusable agent skills
- Create technical presentations, demos, and scalable content (documentation, tutorials, sample code) so solutions can scale globally without extensive hand-holding
- Travel occasionally to partner sites for workshops, technical deep dives, and relationship building
- Help shape team processes and culture as the team scales from 1 to N
Technologies
ClaudeClaude CodeClaude ScienceLLMprompt engineeringcontext engineeringevaluation frameworksagent architecturesretrieval frameworksMCP servers
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