Solution Architect

Solution Architect

As a Solution Architect, you will play a pivotal role in designing and implementing cutting-edge AI and GPU infrastructure solutions. You will work closely with cross-functional teams to ensure that our technology infrastructure supports high-performance computing needs, especially for AI workloads. Your expertise will be crucial in optimizing and scaling our GPU infrastructure to meet the demands of advanced machine learning and data processing tasks.

Responsibilities

• Design and implement GPU infrastructure architecture to support AI and machine learning workloads.
• Deploy and manage GPU clusters using both NVIDIA and AMD GPU architectures.
• Optimize performance and scalability of AI workloads in production environments.
• Develop and deploy multi-node GPU deployments using Kubernetes for orchestration.
• Perform GPU sizing and capacity planning to ensure efficient resource utilization.
• Collaborate with development teams to integrate LLM inference solutions into our infrastructure.
• Utilize Infrastructure as Code (IaC) to automate the deployment and management of GPU infrastructure.
• Conduct technical pre-sales and solution architecture engagements to understand client needs and propose suitable solutions.
• Optimize GPU performance using CUDA and ROCm programming frameworks.
• Administer Linux systems to ensure the stability and security of the infrastructure.
• Develop and maintain Python scripts for automation and monitoring of the infrastructure.

Requirements

• Expertise in GPU Infrastructure Architecture and GPU Cluster Deployment.
• In-depth knowledge of NVIDIA GPU Architecture and AMD Instinct GPU Architecture.
• Experience with LLM Inference and AI Infrastructure Architecture.
• Ability to scale production AI workloads effectively.
• Proficiency in deploying and managing multi-node GPU deployments.
• Strong understanding of Kubernetes for container orchestration.
• Advanced Python Programming skills for automation and scripting.
• Expertise in Linux Administration to manage server environments.
• Knowledge of CUDA and ROCm for GPU performance optimization.
• Experience with Infrastructure as Code (IaC) for automating infrastructure setup.
• Ability to perform GPU Sizing and Capacity Planning for infrastructure design.
• Experience in Technical Pre-Sales and Solution Architecture engagements.

• Experience with GPU Performance Optimization techniques.