Principal Engineer - AI & HPC Solutions Architect
Dell Technologies Saudi Arabia
Computer Hardware Manufacturing · 10,001+ employees
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About the role
You will design, architect, and deploy large-scale AI and HPC cluster infrastructures while providing expert consulting on strategy and operational readiness. Additionally, you will troubleshoot complex performance bottlenecks and develop comprehensive technical documentation to support client engagements.
What they look for
Requirements
Candidates must have proven success in designing and deploying large-scale HPC and AI clusters using NVIDIA, AMD, and Intel technologies. Strong expertise in Linux administration, orchestration tools like Slurm and Kubernetes, and high-performance networking is essential.
Full description
Principal Engineer - AI & HPC Solutions Architect
Dell Technologies is committed to empowering our customers with innovative products and services that enhance their performance and productivity. The Services Solutions Architecture team plays a pivotal role in delivering technical solutions that consistently meet client needs and expectations. As trusted consultants, we partner closely with our clients to understand their objectives and provide infrastructure solutions designed for scalability, efficiency, and future growth.
We invite you to join our Services Solutions Architecture team as a Principal Engineer - AI & HPC Solutions Architect, where you will have the opportunity to excel professionally and make a significant contribution to the advancement of high-performance computing and AI infrastructure.
What you’ll achieve:
As a member of the services delivery team, you will collaborate with Dell consultants, engineering teams, and client stakeholders to design and implement sophisticated AI and HPC cluster architectures. You will design, deploy, optimize, and support large-scale AI infrastructure environments, ensuring technical excellence and customer satisfaction throughout each phase of the engagement.
Responsibilities
You will:
- Design and architect scalable, high-performance compute infrastructures for AI and HPC clusters. Lead the deployment and integration of AI infrastructure solutions utilizing NVIDIA, AMD, and Intel technologies.
- Deploy and manage orchestration tools such as NVIDIA Base Command Manager, Slurm, Kubernetes, and related cluster management platforms. Execute benchmarking, validation, and performance optimization activities utilizing tools such as NCCL, HPL, MLPerf, IO500, and related technologies.
- Provide expert consulting on AI and HPC infrastructure strategy, planning, implementation, and operational readiness. Collaborate with clients to assess technical requirements and deliver customized infrastructure solutions.
- Troubleshoot and resolve complex performance bottlenecks across compute, storage, and network layers. Collaborate with clients to assess technical requirements and deliver customized infrastructure solutions.
- Develop comprehensive documentation including architecture diagrams, deployment guides, technical designs, and operational procedures. Act as a trusted technical advisor throughout the customer engagement lifecycle.
Qualifications
Essential Requirements
- Proven success in designing and deploying large-scale HPC and AI clusters utilizing NVIDIA, AMD, and Intel technologies.
- Strong experience with Linux systems administration, troubleshooting, and automation. Extensive hands-on experience with NVIDIA Base Command Manager, Slurm, Kubernetes, or equivalent orchestration platforms.
- Experience with high-performance networking technologies including InfiniBand and RoCE. Experience performing system benchmarking, performance validation, and optimization activities.
- Demonstrated ability to manage multiple projects independently and deliver results within dynamic environments. Strong customer-facing communication and consulting skills.
Desirable Requirements
- Experience with NVIDIA DGX and DGX SuperPOD platforms. Familiarity with AI/ML and Generative AI infrastructure environments. Knowledge of containerized AI platforms and software stacks.
- Experience with Python, Ansible, Terraform, or similar automation technologies. Knowledge of data center operations, networking, storage architectures, and cloud integration methods. Experience supporting GPU clusters comprising thousands of accelerators.
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