Director, AI Platform Architecture & Engineering

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.

Your new role 

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.

Your main responsibilities include:

AI Platform Strategy and Leadership

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

Architecture and Engineering

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

Advanced Compute and HPC Infrastructure

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

Storage and Data Infrastructure

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

MLOps, LLMOps, and Responsible AI

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

Stakeholder and Vendor Management

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

Your Skills and Qualifications 

• 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

Strong technical background with expertise in:

• AWS, Azure, or GCP