Associate Director - HPC Infrastructure Architect

Key Responsibilities:

• Own the HPC reference architecture: cluster topologies, CPU and GPU node designs, high-performance and tiered storage, interconnect fabric, schedulers and the software stack that supports scientific workflows.
• Define the scientific workload placement model - which workloads run on dedicated clusters, which burst to cloud, and which belong on AI platforms - based on performance, data gravity, cost and compliance.
• Produce and maintain capacity plans for compute, accelerators, storage and network, including the power, rack and cooling requirements that data centre and colocation planning depends on.
• Establish data-locality and data-movement principles across instruments, laboratories, storage tiers, archive and cloud, including replication and recovery approaches for irreplaceable scientific data.
• Translate scientific requirements into sizing, benchmarking and procurement input, and validate feasibility before engineering build.
• Maintain architecture decision records for HPC platform choices, connecting each to scientific outcome, cost and lifecycle consequence.
• Define the interface with AI infrastructure so that shared accelerators, storage and data pipelines are used coherently rather than duplicated.
• Ensure HPC designs meet security, quality and regulatory expectations and are operable by Infrastructure Operations after handover.
• Engage scientific communities and research IT partners as the trusted architecture contact for high-performance computing.
• Coach engineers and analysts, and act as a role model for the Novartis Values and Behaviours.

Essential Requirements:

• 8+ years of experience designing, building, or operating large-scale High-Performance Computing (HPC) environments.
• Proven expertise in HPC platform architecture, capacity planning, and multi-cluster infrastructure design.
• Strong experience supporting Linux-based compute clusters in enterprise or scientific computing environments.
• Hands-on knowledge of workload schedulers such as Slurm, LSF, or comparable HPC scheduling technologies.
• Solid understanding of CPU and GPU infrastructure design, performance optimization, and benchmarking methodologies.
• Experience with high-performance storage solutions, parallel file systems, and high-speed networking technologies, including InfiniBand and Ethernet fabrics.
• Knowledge of containerized, reproducible scientific workflows and hybrid or cloud-based HPC environments.
• Familiarity with large-scale data management practices, including data replication, archiving, and infrastructure planning (power, cooling, and rack design); experience supporting research or scientific computing communities is highly desirable.

Desirable Requirements:

• Able to work fluently with scientists and translate research needs into infrastructure terms; rigorous, evidence-based approach to sizing and benchmarking; long-horizon planning discipline; strong collaboration across engineering, facilities and research organizations.
• Fluent English, written and spoken. Additional languages are an asset.

You’ll receive: You can find everything you need to know about our benefits and rewards in the Novartis Life Handbook. https://www.novartis.com/careers/benefits-rewards

Commitment to Diversity and Inclusion:  
Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.  

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