Global Head of Technology & Architecture in Biomedical Research; BR

Location:

Cambridge, USA. Hybrid 3 days/week in office. This role requires being in our Cambridge US office 3×/week. Internal job title:
Global Head   Technology, Foundations & Architecture.

The Global Head of Technology & Architecture in Biomedical Research (BR) will spearhead our Information Technology strategy in drug discovery and early clinical development, ensuring technologies align with objectives while promoting unity and cooperation with internal and external partners, transforming our global labs into high‑throughput, AI‑orchestrated environments. By integrating “dry lab” hypothesis generation with “wet lab” robotic validation, you will build the “Self‑Driving Lab” of the future.

The leader will be a member of the Biomedical Research Data & Digital Leadership Team and a matrixed member of the Data, Digital, and IT (DDIT) leadership team representing the needs of Biomedical Research. The role reports to the Chief Data & Digital Officer,   and works closely with the Data and Digital leadership team.

• Deliver top-tier research informatics to expedite discovery of new treatments using data & digital technology and enhance researcher user experience.
• Ensure evolution of  ’s technology capabilities, underlying architecture, and make-or-buy decisions for software products and architecture in close alignment with DDIT to deliver harmonized, scalable, end‑to‑end approaches across projects.
• Lead strategy, design, and evolution of next‑generation Data & AI Platforms for a global biomedical research organization, define multi‑year vision and roadmap for Research Data & AI Platforms, ensuring alignment with scientific priorities and digital AI strategy.
• Contribute to the global digital strategy for  ’s AI‑driven drug discovery using Data Science, Gen AI, and ML on the technology side, and participate in key strategic cross‑divisional data and digital projects and initiatives to ensure seamless compatibility of data systems and solutions across Novartis Research‑Development and Commercial units.
• Drive the lab of the future initiative from an informatics perspective alongside lab equipment and automation experts from other   functions.
• Collaborate closely with Novartis DDIT and the   Data Science community to devise and execute the digital and AI strategy for  , ensuring   is a fully AI‑enabled Research Organization.
• Evaluate emerging technologies (agentic workflows, vector databases, GPU infrastructure, lab digitalization technologies, quantum computing, etc.) and translate them into practical capabilities that drive research outcomes; lead platform architecture reviews and steer technology selection.
• Provide strategic input and vision on technologies to the President of Research and  ’s scientific leadership, acting as a recognized advisor to top management.
• Partner closely with DDIT functions to ensure enterprise solutions are preferentially deployed where possible and seek synergies; serve as a bridge between engineering, R&D scientists, data science, and IT security/compliance and infrastructure groups.
• Grow and lead a diverse, inclusive, high‑performing team and instill a collaborative, enterprise mindset, developing and mentoring high‑performing, diverse team of platform engineers, software engineers, domain specialists, architects, and lab technologists.

• PhD or master’s degree in computer science, data science, AI, computational biology, cheminformatics, or a related discipline.
• Background spanning both technology and life sciences is strongly preferred.
• 12+ years of experience in platform engineering, architecture, infrastructure, data engineering, cloud architecture, research lab technologies or ML infrastructure; with 8+ years in leadership roles.
• Strong understanding of modern AI/ML workflows, including LLMs, model training/serving, monitoring, MLOps, and GPU infrastructure.
• Expertise with cloud-native architectures, microservices, APIs, Kubernetes, IaC, observability tools, and high-performance computing.
• Familiarity with scientific research workflows and associated data modalities (omics, imaging, real‑world data, lab‑generated data).
• Experien…