Platform Architecture Director

Hybrid

Are you passionate about advancing treatments for chronic diseases such as diabetes and obesity and improving patient outcomes? Do you have strong experience designing and engineering AI platforms, advanced compute, and storage infrastructure in a regulated environment? Join Novo Nordisk and help build the secure, scalable foundations that enable responsible AI across research, clinical development, and the enterprise.

Lead the architecture, engineering, and operations of AI platforms and advanced compute and storage infrastructure across Novo Nordisk’s R&D and enterprise ecosystem. Build the foundations that allow scientists, data scientists, ML engineers, and product teams to accelerate drug discovery, clinical development, and business outcomes through scalable, compliant, and responsible AI.

• Own the AI platform vision, target architecture, roadmap, engineering strategy, and operating model
• Define enterprise standards for GenAI, Agentic AI, foundation models, MLOps, LLMOps, platform reliability, and responsible AI
• Drive adoption across research, pre-clinical, clinical, and business functions

• Lead architecture and engineering teams responsible for AI/ML platforms, data platforms, AI infrastructure, cloud platforms, Kubernetes, and platform operations
• Deliver secure, scalable, observable, and cost-effective AI services across cloud, hybrid cloud, and on-premises environments

• Design and operate GPU, supercomputing, and high-performance computing environments for foundation-model training, inference, simulation, and other data-intensive workloads
• Define capacity, procurement, workload placement, performance, availability, sustainability, and cost-management strategies

• Lead the architecture and engineering of petabyte-scale storage, data movement, backup, archival, lifecycle, governance, and high-performance data services
• Ensure storage and data platforms provide the throughput, resilience, security, compliance, accessibility, and cost efficiency required by AI and scientific workloads

• Enable reliable model development, training, deployment, inference, monitoring, auditability, explainability, and lifecycle management
• Establish AI governance frameworks, model risk controls, and compliance practices appropriate to a regulated pharmaceutical environment

• Partner with R&D, research, clinical-development, enterprise, and technology leaders to translate strategic needs into production capabilities
• Manage strategic relationships across cloud, GPU, storage, networking, Kubernetes, MLOps, LLM platforms, and HPC ecosystems

• Educational background in software engineering, computer science, data, AI, infrastructure, or platform engineering leadership.
• Experience leading global teams
• Experience building and operating enterprise AI platforms, advanced compute, HPC, or storage infrastructure at scale.
• Experience in a highly regulated industry, with pharmaceutical or life-sciences experience preferred

• AWS, Azure, or GCP
• Kubernetes and cloud platform engineering
• AI/ML, MLOps, and LLMOps platforms
• GenAI, Agentic AI, and foundation models
• Data engineering, distributed systems, and Python ecosystems
• GPU, HPC, advanced compute, and high-performance storage
• Infrastructure as code, Dev Ops, Data Ops, security, and observability

Every day we seek the solutions that defeat serious chronic diseases. To do this, we approach our work with an unconventional spirit, a rare determination and a…