Director, Technology & Engineering – Software & Workflows

About the role

As Director of Technology & Engineering within Novartis Biomedical Research Data & Digital Software & Workflows, you will lead the creation of AI‑enabled software that accelerates scientific discovery. Based in Basel, you will shape technical direction, build high‑performing teams and ensure delivery of reliable, secure solutions that support laboratory and research workflows.

Key responsibilities

• Define and communicate a clear technology vision that links engineering priorities to scientific impact and corporate strategy.
• Coach and develop engineering managers, technical leaders and AI engineering talent, fostering a learning culture and high performance.
• Drive adoption of modern AI‑enabled engineering practices, including DevOps, CI/CD, test automation and observability.
• Ensure architecture, security, compliance and responsible AI governance align with enterprise standards.
• Partner with delivery, architecture, operations, security and vendor teams to turn diverse inputs into coordinated action and predictable delivery.
• Own execution of a portfolio of time‑bound software initiatives, managing scope, budget, risk and resource trade‑offs.

Required profile

• Proven experience leading technology functions and multidisciplinary software teams in a global, matrixed environment.
• Strong learning mindset with ability to explore emerging technologies and translate insights into action.
• Strategic agility to connect long‑term direction with near‑term priorities and adapt to evolving circumstances.
• Track record of delivering large‑scale SaaS, cloud‑based and on‑premises solutions with measurable impact.
• Excellent communication and influencing skills, capable of engaging senior leaders and simplifying technical complexity.
• Leadership style based on integrity, empowerment, accountability and commitment to developing others.

Required skills

• AI‑enabled software engineering practices
• DevOps and continuous integration/continuous delivery (CI/CD)
• Test automation and observability
• Agile or Lean delivery methodologies
• Cloud platforms and SaaS development
• On‑premises software architecture
• Integration of AI models and agents into production systems
• Scalable architecture and operational excellence