Associate Director - HPC Infrastructure Architect

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About the role

Salary Range: Kč1,120,210.00 - Kč2,080,390.00   Job Description Summary Scientific computing sits at the centre of how Novartis discovers and develops medicines. Cloud & Hosting Services has established AI & HPC Engineering as the single engineering and delivery channel for high-performance computing, and Architecture & Integration owns the target architecture behind it. The HPC Infrastructure Architect is accountable for that architecture: the compute, storage, interconnect, scheduling and data-locality design that scientific workloads run on, on premises and in the cloud. The role translates scientific demand - molecular modelling, imaging and cryo-electron microscopy, genomics, simulation and increasingly AI-adjacent workloads - into capacity models, workload placement principles and platform patterns. It carries the physical dependencies with it: power, rack and cooling envelopes, high-performance storage tiers, network fabric, and the data centre and colocation footprint that a large campus and site transformation programme is reshaping. This is an individual contributor architecture role in which credibility with scientists matters as much as credibility with infrastructure engineers.   Job Description 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

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