AI Data Center Architect
Intellectt INC
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Job Details
Skills
- Scalability
- Resource Management
- Software Design
- Presentations
- Technical Writing
- InfiniBand
- Spectrum
- Capacity Management
- Kubernetes
- Scheduling
- Machine Learning (ML)
- Machine Learning Operations (ML Ops)
- Generative Artificial Intelligence (AI)
- Computer Networking
- Storage
- GPU
- Cloud Computing
- Microsoft Azure
- Amazon Web Services
- Google Cloud
- Google Cloud Platform
- Training
- Orchestration
- Artificial Intelligence
- Benchmarking
- Performance Tuning
- Customer Facing
- Sales
- Billing
Summary
Location: Plano, TX
Job Summary
We are seeking a highly skilled AI Data Center Architect with hands-on experience designing and architecting modern AI infrastructure at enterprise or hyperscale scale.
This is not a traditional enterprise data center architecture role. The ideal candidate will have deep expertise in GPU infrastructure, AI Factories, GPU-as-a-Service (GPUaaS), NVIDIA reference architectures, high-performance networking, AI storage, Kubernetes, and large-scale AI/LLM workloads.
The successful candidate will be responsible for designing end-to-end AI infrastructure solutions, including GPU compute, high-performance networking, storage, orchestration, multi-tenancy, and AI platform services. The individual should be comfortable working directly with customers and technical stakeholders to translate AI workload requirements into scalable infrastructure architectures.
Key Responsibilities
- Design and architect enterprise and hyperscale AI Factory environments from the ground up.
- Develop scalable GPU infrastructure and GPU-as-a-Service (GPUaaS) architectures.
- Design infrastructure for large-scale AI training, inference, LLM, and GenAI workloads.
- Develop solutions based on NVIDIA Enterprise Reference Architectures.
- Architect NVIDIA GPU platforms including DGX, HGX, H200, GB200, and Blackwell systems.
- Design high-performance AI networking using InfiniBand, RoCE, Spectrum-X, NVLink, and BlueField DPUs.
- Perform GPU cluster sizing, capacity planning, performance optimization, and scalability analysis.
- Design high-performance storage architectures capable of supporting large-scale GPU and AI workloads.
- Architect Kubernetes-based AI platforms, including GPU scheduling, workload orchestration, resource management, and multi-tenancy.
- Design distributed training and inference infrastructure for modern LLM and GenAI workloads.
- Develop architectures for AI Cloud, GPU Cloud, and on-premises AI Factory deployments.
- Evaluate infrastructure requirements across compute, networking, storage, orchestration, and AI platform layers.
- Work with engineering, infrastructure, cloud, networking, and AI/ML teams to develop end-to-end solutions.
- Participate in customer-facing architecture discussions, technical workshops, solution design, and presentations.
- Create high-level and low-level architecture designs, technical documentation, reference architectures, and solution proposals.
- Evaluate emerging NVIDIA technologies and AI infrastructure trends and incorporate them into future architectures.
Required Qualifications
- 4+ years of experience designing AI-focused infrastructure, accelerated computing platforms, or GPU-based data center environments.
- Proven experience architecting AI Factories, GPU clusters, or GPUaaS platforms.
- Experience designing environments supporting 100+ GPUs is strongly preferred.
- Deep understanding of NVIDIA AI infrastructure and Enterprise Reference Architectures.
- NVIDIA DGX
- NVIDIA HGX
- H200
- GB200
- NVIDIA Blackwell platforms
- InfiniBand
- Spectrum-X
- RoCE
- NVLink / NVSwitch
- BlueField DPUs
- 400G/800G networking
- Experience with GPU cluster sizing, performance optimization, scaling, and capacity planning.
- Strong understanding of LLM training and inference infrastructure.
- Experience with Kubernetes for AI/GPU workloads.
- Knowledge of GPU scheduling, workload orchestration, and multi-tenant GPU environments.
- Experience designing distributed AI/ML training infrastructure.
- Strong knowledge of high-performance storage architectures for AI workloads.
- Understanding of MLOps, AI platforms, and GenAI infrastructure.
- Ability to design complete AI infrastructure solutions spanning compute, networking, storage, orchestration, and platform services.
Preferred Qualifications
- Experience designing on-premises AI Factories, Sovereign AI infrastructure, or GPU Cloud platforms.
- Experience with Azure, AWS, or Google Cloud AI infrastructure.
- Experience with NVIDIA AI Enterprise and the broader NVIDIA AI software ecosystem.
- Experience with large-scale distributed training frameworks and AI workload orchestration.
- Experience with AI infrastructure benchmarking and performance optimization.
- Customer-facing architecture, consulting, solution engineering, or technical pre-sales experience.
- Experience developing technical proposals, architecture diagrams, bills of materials, and solution designs.
- Dice Id: 91111992
- Position Id: 2026-42407
- Posted 1 day ago
Company Info
Intellectt Inc. is a global IT and next-generation engineering solutions company
that helps graded enterprises innovate, scale, and stay competitive in a digital-first world. We
combine deep domain expertise with advanced engineering, digital, and manufacturing
capabilities to solve complex challenges across industries such as Healthcare, BFSI, Aerospace,
Automotive, Manufacturing, Telecom, Retail, and Energy. With a team of 2,500+ professionals, including 1,800+ engineers, and 15 global delivery centers across the USA, India, Canada, Mexico, Ireland, and Asia, Intellectt delivers high-quality, scalable solutions. The company has achieved an annual revenue of $270 million, reflecting strong growth and client trust. Our core capabilities include Engineering & Manufacturing, Validation & Quality, Digital Technologies, Healthcare Solutions, Enterprise Applications, Managed Services, and Talent Solutions. We bring expertise in AI, Data & Analytics, Cloud, IoT, Digital Twins, SAP, and Industry 4.0, along with strong capabilities in regulated environments such as medical devices and life sciences. Driven by agility, quality, and innovation, Intellectt partners with organizations to deliver efficient, compliant, and future-ready solutions that create measurable business impact.
With 30+ years of combined engineering and manufacturing expertise across its
divisions, Intellectt brings deep domain knowledge and execution maturity, enabling clients to
confidently navigate complex, regulated, and high-performance environments.
Flagship Platforms & Accelerators :
Intellectt has developed advanced proprietary solutions and accelerators to drive business
efficiency and innovation, including:
● Voice Connector - enabling seamless, intelligent communication systems
● CCMA (Customer Communication Management & Automation) - delivering
personalized, automated customer engagement at scale
● Enterprise Data Platforms & AI Accelerators - enabling faster deployment of
data-driven and AI-powered solutions
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