Introduction

IBM Infrastructure is a catalyst that makes the world work better because our clients demand it. Heterogeneous environments, the explosion of data, digital automation, and cybersecurity threats require hybrid cloud infrastructure that only IBM can provide. Your ability to be creative, a forward-thinker and to focus on innovation that matters, is all supported by our growth-minded culture as we continue to drive career development across our teams. Collaboration is key to IBM Infrastructure success, as we bring together different business units and teams that balance their priorities in a way that best serves our clients needs. IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive.

The Mission Of The IBM Storage Solutions Team Is To Engage With Strategic ISV And OEM Partners That May Advance The IBM Storage Strategy To Expand The Marketability Of The Portfolio, Create Short- And Long-term Alignment Of Solutions Roadmaps, And Engage In Collaborative GTM. The Team Will

Engage with the entire IBM Storage brand – product managers, engineers, technologists, researchers, marketers, and sellers - and the same with our technology partners worldwide

Prioritize and lead strategic client engagements with solutions engineering expertise

Design, build, and operate a world-class strategically-aligned ISV program

Our primary intention is to realize measurable, material, incremental business for the Storage product team accredited to our joint in-market solutions with technology partners.

This group is comprised of technology and business professionals who are intent on bringing to market impactful customer solutions based on the IBM Storage assets of today and the future. It will have influence over our product roadmaps and will evangelize everything we have to offer to our partners, our clients, and the worldwide market broadly.

Your Role And Responsibilities

Architecting and deploying high-performance data environments for large-scale AI training and inference. It requires one to design, build, and maintain high-performance storage systems for AI/ML workloads, bridging storage tech with AI needs (GPU clusters, data pipelines), requiring skills in infrastructure automation, performance tuning , cloud platforms, and collaboration with data scientists to ensure scalable, secure, and reliable data flow for complex models.
Engage with the entire IBM Storage brand – product managers, engineers, technologists, researchers, marketers, and sellers - and the same with our technology partners worldwide
Design, develop, build, integrate, and test, validate, or otherwise certify differentiated workload-based solutions based on the IBM Storage portfolio of offerings combined with 3rd party technology from leading technology partners
Contribute to defining clear requirements for the IBM Storage portfolio based on industry trends and key ISV and OEM partner strategies, in collaborative partnership with Storage Product Managers
Educate the market on the critical vitality of IBM Storage to the successful deployment and performance of business-valued workloads
Provide education to customers and sales regarding our storage solutions in a wide variety of formats (e.g., blogs, white papers, reference architectures, videos, industry social media, trade shows, on-site briefings, etc.)
Drive client success stories, references, and joint marketing opportunities between IBM Storage and our technology partners
Help foster the feeling of being a trusted advisor with our customers when it comes to strategic storage solutions
Leverage AIdriven tools and automation to solve everyday business problems, support datainformed decisionmaking, and significantly enhance team productivity
Enable cross-selling of jointly developed storage solutions in the market
Architecture & Design: Lead end-to-end system design for distributed storage platforms tailored to AI/HPC workloads.
Performance Optimization: Maximize IOPS and throughput for multi-node GPU clusters, ensuring storage systems can keep up with the demands of deep learning frameworks
Infrastructure Automation: Build CI/CD and automation pipelines for provisioning and monitoring AI infrastructure using tools like Terraform, Ansible, and Kubernetes.
Solution Selection, Validation and Publishing : Evaluate and select next-generation storage technologies such as NVMe-oF (IBM Flashsystems), Ceph to support petabyte-scale data.
AIOps Integration: Build CI/CD pipelines, monitoring and orchestration (Kubernetes) for AI/ML workflows.

Preferred Education

Master's Degree

Required Technical And Professional Expertise

Experience: Typically 12-15 years in AI Infrastructure, systems engineering and/or storage architectures.

Strong Expertise with NVIDIA DGX/HGX systems, GPUs, and DPUs (e.g., NVIDIA BlueField) for storage-offloading

Understanding and hands on experience of working with SAN, NAS, and Parallel File Systems (IBM Storage preferred) alongside protocols like NFS, SMB, and S3.

Proficiency in Linux, Networking and Storage Systems.

Sound understanding of data modelling, governance, and security frameworks.

Experience deploying hybrid or multi-cloud AI solutions on HCI, AWS, Azure, or GCP and virtualization technologies such as Kubernetes, RHOS, VMWare.

Automation/Scripting: Proficiency in Python, Bash, or Go for developing custom monitoring and management tools.

Excellent problem-solving and communication skills.

Ability to apply AIdriven tools for rapid problemsolving, databased decisions, and productivity improvement.

Experience in HA/DR design and implementations.

Preferred Technical And Professional Experience

Deep Domain Knowledge: Experience with analyzing market trends, user problems, and market dynamics to inform business strategies and identify opportunities.
Technical Asset Creation: Exposure to designing and delivering technical assets that effectively demonstrate user experience and offering value propositions.
Product Portfolio Understanding: Experience with translating market needs into development plans based on a thorough understanding of product portfolio capabilities.

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