AI Infrastructure Storage Solutions Architect

About the Role

IBM Infrastructure is seeking a creative and innovative AI Infrastructure Storage Solutions Architect. This role is crucial in designing and implementing high-performance data environments for large-scale AI training and inference. You will work at the heart of IBM, contributing to a growth-minded culture focused on innovation and career development. Collaboration with various business units, product teams, and technology partners worldwide is key to success.

Mission of the IBM Storage Solutions Team

The mission is to engage with strategic ISV and OEM partners to advance IBM Storage strategy, expand portfolio marketability, align solution roadmaps, and collaborate on Go-To-Market (GTM) initiatives. This involves working closely with IBM's internal teams (product managers, engineers, researchers, marketers, sellers) and external technology partners to realize measurable business growth through joint solutions.

Your Role and Responsibilities

• Architect, design, build, and operate high-performance storage systems tailored for AI/ML workloads.
• Bridge the gap between storage technology and AI needs, including GPU clusters and data pipelines.
• Implement infrastructure automation, performance tuning, and cloud platform solutions.
• Collaborate with data scientists to ensure scalable, secure, and reliable data flow for complex models.
• Design, develop, integrate, and test differentiated workload-based solutions using the IBM Storage portfolio and third-party technologies.
• Contribute to defining storage portfolio requirements based on industry trends and partner strategies.
• Educate the market, customers, and sales teams on the importance of IBM Storage for business-valued workloads through various formats (blogs, white papers, reference architectures, videos, social media, trade shows).
• Drive client success stories, references, and joint marketing opportunities.
• Act as a trusted advisor for strategic storage solutions.
• Leverage AI-driven tools and automation to solve business problems, support data-informed decisions, and enhance team productivity.
• Enable cross-selling of jointly developed storage solutions.
• Lead end-to-end system design for distributed storage platforms for AI/HPC workloads.
• Maximize IOPS and throughput for multi-node GPU clusters using deep learning frameworks.
• Build CI/CD and automation pipelines for provisioning and monitoring AI infrastructure (Terraform, Ansible, Kubernetes).
• Evaluate and select next-generation storage technologies (e.g., NVMe-oF, Ceph) for petabyte-scale data.
• Integrate AIOps for AI/ML workflows, including CI/CD pipelines, monitoring, and orchestration (Kubernetes).

Key Skills and Competencies

Storage Solutions Architect, AI Infrastructure, High-Performance Computing (HPC), Machine Learning (ML), Deep Learning, Data Pipelines, Infrastructure Automation, Performance Tuning, Cloud Platforms, Kubernetes, Terraform, Ansible, NVMe-oF, Ceph, NVIDIA DGX, GPUs, DPUs, SAN, NAS, Parallel File Systems, NFS, SMB, S3, Linux, Python, Bash, Go, HA/DR.