AI Infrastructure Solution Architect

We are looking for a technically skilled and customer-centric AI Infrastructure Solutions Architect to lead the design and positioning of AI solutions built on NVIDIA and HPE platforms. This role focuses on enabling enterprise and public sector customers to deploy scalable, high-performance AI infrastructure using NVIDIA GPUs, software stacks, and HPE compute, storage, and networking technologies.

Key Responsibilities:

1. AI Hardware Architecture

• Design AI compute clusters using the likes of NVIDIA GPUs (e.g., H100, A100, L40S) integrated into the likes of HPE Apollo, Cray, and ProLiant platforms or others.
• Recommend server configurations including HPE GreenLake for HPC & AI, HPE Machine Learning Development Environment, NVIDIA systems and others.
• Architect high-speed interconnects using NVIDIA NVLink, InfiniBand, and HPE Slingshot for distributed training workloads.
• Size and optimize storage solutions using HPE Alletra, HPE Ezmeral Data Fabric, NVIDIA GPUDirect Storage and others.

2. AI Software Stack & Integration

• Architect AI/ML environments using NVIDIA AI Enterprise, CUDA, cuDNN, and TensorRT.
• Integrate Container Platforms and Kubernetes for scalable AI workloads.
• Design MLOps pipelines using NVIDIA Base Command, MLflow, and Kubeflow.
• Ensure compatibility with AI frameworks (e.g., PyTorch, TensorFlow) and job schedulers (e.g., Slurm, Ray).

3. Presales Engagement & Technical Enablement

• Collaborate with account teams to understand customer requirements and translate them into client aligned solutions.
• Deliver technical presentations, demos, and workshops focused on AI infrastructure.
• Lead Proof-of-Concept (PoC) deployments and performance benchmarking using NVIDIA NGC containers and infrastructure systems.
• Create architecture diagrams, BOMs, and solution briefs tailored to customer use cases.

4. Hybrid & Cloud AI Infrastructure

• Design hybrid AI infrastructure leveraging the likes of HPE HPC, NVIDIA AI Cloud Services, and public cloud platforms (Azure, AWS, GCP).
• Advise on cloud-native AI services and integration with on-prem NVIDIA/HPE workloads.
• Support discussions around data gravity, latency, and cost optimization in hybrid deployments.

5. Partner & Ecosystem Collaboration

• Work closely with NVIDIA, HPE, and ecosystem partners to co-develop and position joint AI solutions.
• Stay current with emerging NVIDIA and HPE technologies, product roadmaps, and industry trends.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Engineering, Data Science, or related field.
• 5+ years of experience in infrastructure architecture, with a focus on AI/ML workloads.
• Deep understanding of GPU compute, high-performance storage, and networking.
• Experience with NVIDIA AI software stack, HPE infrastructure, and container orchestration.
• Strong communication and customer engagement skills.

Preferred Qualifications:

• Certifications in cloud or infrastructure architecture (e.g., NVIDIA Certified, HPE ASE, Azure/AWS/GCP Architect).
• Experience with NVIDIA DGX systems, HPE HPC, and AI workload benchmarking.
• Familiarity with data governance, security, and compliance in AI environments.
• Prior experience in presales, technical consulting, or solution architecture.

Why Join Us?

• Shape the future of enterprise AI infrastructure with industry leaders like NVIDIA and HPE.
• Work with cutting-edge hardware and software technologies.
• Collaborate with innovative customers and partners across industries.
• Be part of a high-impact team driving AI transformation.