مهندس رئيسي أول - معماري حلول الذكاء الاصطناعي والحوسبة عالية الأداء

Senior 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 Senior Principal Engineer - AI & HPC Solutions Architect, where you will have the opportunity to lead the design and deployment of some of the industry's largest and most advanced AI infrastructure environments.

Key Responsibilities

As a senior member of the services delivery team, you will collaborate with Dell consultants, engineering teams, and executive customer stakeholders to design and implement large-scale AI and HPC architectures. You will serve as the technical lead for highly complex deployments, driving architecture, implementation, optimization, and operational readiness for enterprise and hyperscale AI environments.

Responsibilities

You will:

• Design and architect highly scalable AI and HPC infrastructures supporting large-scale model training and inference workloads.
• Lead architecture and implementation activities for enterprise and hyperscale AI environments utilizing NVIDIA, AMD, and Intel technologies.
• Design and implement large GPU clusters supporting several thousand to tens of thousands of accelerators.
• Lead deployment and optimization of orchestration platforms including NVIDIA Base Command Manager, Slurm, Kubernetes, and related technologies.
• Drive large-scale benchmarking, validation, performance engineering, and scalability testing activities utilizing tools such as NCCL, HPL, MLPerf, IO500, and related technologies.
• Provide expert consulting on AI factory architecture, infrastructure scalability, platform engineering, and operational strategy.
• Collaborate with customer technical leadership to define long-term AI infrastructure roadmaps and deployment strategies.
• Lead resolution of the most complex performance, scalability, and integration challenges across compute, storage, networking, and software layers.
• Provide technical leadership and mentorship to other architects and engineers supporting major programs.
• Develop comprehensive documentation including architecture diagrams, deployment guides, technical designs, and operational procedures.
• Act as the senior technical authority and trusted advisor throughout strategic customer engagements.

Qualifications

Essential Qualifications

• 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.
• Deep expertise with high-performance networking technologies including InfiniBand and RoCE.
• Extensive experience performing system benchmarking, scalability testing, performance validation, and optimization activities.
• Demonstrated success architecting and deploying large-scale GPU environments comprising thousands of accelerators.
• Experience leading highly complex customer engagements and technical workstreams.
• Strong customer-facing communication, consulting, and technical leadership skills.
• Ability to manage multiple large-scale projects and influence technical decisions across diverse stakeholder groups.

Desirable Qualifications

• Experience with NVIDIA DGX, DGX SuperPOD, and AI Factory architectures.
• Expertise in AI/ML and Generative AI infrastructure environments.
• Experience supporting GPU deployments comprising tens of thousands of accelerators.
• Experience with large-scale LLM training and inference environments.
• Experience with Python, Ansible, Terraform, or similar automation technologies.
• Knowledge of advanced data center design, networking, storage architectures, and cloud integration methods.
• Experience mentoring architects and leading technical teams across complex infrastructure programs.