Sales Solutions Architect: Storage & AI Professional Multiple Cities
IBM, Chicago, IL, United States
Overview
Senior Storage Architect focusing on AI infrastructure opportunities. Bridge the gap between high-performance storage and high-speed networking, out-architect competitors, and act as a trusted advisor to CIOs and CTOs during solution design. Optimize the data path from storage through the network to the GPU for maximum throughput and minimum latency. Key Responsibilities
Executive Technical Advisory:
Partner with CIOs, CTOs, and IT Directors to align storage and networking strategy with business AI goals, focusing on eliminating I/O bottlenecks and maximizing GPU investment. Competitive Displacement:
Proactively identify and exploit architectural weaknesses in VAST Data, Weka, and DDN. Lead the technical win by proving IBM's superiority in scalability, parallel data access, and fabric efficiency. End-to-End AI Infrastructure Design:
Architect high-performance data pipelines, integrating IBM Storage Scale (GPFS) with NVIDIA DGX/SuperPOD systems, ensuring seamless integration with high-speed network fabrics. Network Fabric Optimization:
Design and troubleshoot high-performance networking for AI, including InfiniBand and RoCE (RDMA over Converged Ethernet) architectures to support GPUDirect Storage (GDS). Technical Closure:
Lead high-visibility Proof of Concepts (POCs) and performance bake-offs. Own the technical success of the sales cycle, proving performance at scale. Value-Based Selling:
Collaborate with Sales Specialists to create compelling business cases, translating technical throughput and networking efficiency into tangible ROI for the client. Qualifications and Experience
Required education:
High School Diploma/GED. Required technical and professional expertise:
Extensive experience in Technical Pre-Sales, Architecture, or Sales Engineering for Enterprise Storage or High-Performance Networking. Storage Scale Mastery:
Expert-level knowledge of IBM Storage Scale (GPFS) architecture, deployment, and performance tuning. Networking Expertise:
Deep, hands-on experience with InfiniBand (Mellanox/NVIDIA) and High-Speed Ethernet (RoCE v2). Must understand subnet managers, adaptive routing, and fabric congestion management. Competitive Intelligence:
Proven experience competing against or managing solutions from VAST Data, Weka, or DDN (EXAScaler/Lustre). AI Infrastructure:
Extensive experience designing storage for NVIDIA GPU environments, including GPUDirect Storage (GDS) and RDMA-enabled data paths. C-Suite Presence:
Demonstrated ability to present and defend complex technical architectures to Executive-level leadership. Cloud Native Foundations:
Proficiency in Red Hat OpenShift and Kubernetes for orchestrating data-intensive AI/ML workloads. Preferred Qualifications
Experience with NVIDIA Quantum (InfiniBand) and Spectrum (Ethernet) switch architectures. Knowledge of POSIX, NFS over RDMA, and S3/Object storage protocols. Experience in data-heavy verticals (Finance/HFT, Life Sciences, Autonomous Research). Industry certifications such as NVIDIA Certified Associate/Professional (Networking) or equivalent. Certifications and Technical Skills
OpenShift and Kubernetes proficiency; knowledge of GPUDirect Storage (GDS) and RDMA-enabled data paths. EEO Statement
IBM is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by applicable law. IBM is also committed to compliance with fair employment practices regarding citizenship and immigration status.
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Senior Storage Architect focusing on AI infrastructure opportunities. Bridge the gap between high-performance storage and high-speed networking, out-architect competitors, and act as a trusted advisor to CIOs and CTOs during solution design. Optimize the data path from storage through the network to the GPU for maximum throughput and minimum latency. Key Responsibilities
Executive Technical Advisory:
Partner with CIOs, CTOs, and IT Directors to align storage and networking strategy with business AI goals, focusing on eliminating I/O bottlenecks and maximizing GPU investment. Competitive Displacement:
Proactively identify and exploit architectural weaknesses in VAST Data, Weka, and DDN. Lead the technical win by proving IBM's superiority in scalability, parallel data access, and fabric efficiency. End-to-End AI Infrastructure Design:
Architect high-performance data pipelines, integrating IBM Storage Scale (GPFS) with NVIDIA DGX/SuperPOD systems, ensuring seamless integration with high-speed network fabrics. Network Fabric Optimization:
Design and troubleshoot high-performance networking for AI, including InfiniBand and RoCE (RDMA over Converged Ethernet) architectures to support GPUDirect Storage (GDS). Technical Closure:
Lead high-visibility Proof of Concepts (POCs) and performance bake-offs. Own the technical success of the sales cycle, proving performance at scale. Value-Based Selling:
Collaborate with Sales Specialists to create compelling business cases, translating technical throughput and networking efficiency into tangible ROI for the client. Qualifications and Experience
Required education:
High School Diploma/GED. Required technical and professional expertise:
Extensive experience in Technical Pre-Sales, Architecture, or Sales Engineering for Enterprise Storage or High-Performance Networking. Storage Scale Mastery:
Expert-level knowledge of IBM Storage Scale (GPFS) architecture, deployment, and performance tuning. Networking Expertise:
Deep, hands-on experience with InfiniBand (Mellanox/NVIDIA) and High-Speed Ethernet (RoCE v2). Must understand subnet managers, adaptive routing, and fabric congestion management. Competitive Intelligence:
Proven experience competing against or managing solutions from VAST Data, Weka, or DDN (EXAScaler/Lustre). AI Infrastructure:
Extensive experience designing storage for NVIDIA GPU environments, including GPUDirect Storage (GDS) and RDMA-enabled data paths. C-Suite Presence:
Demonstrated ability to present and defend complex technical architectures to Executive-level leadership. Cloud Native Foundations:
Proficiency in Red Hat OpenShift and Kubernetes for orchestrating data-intensive AI/ML workloads. Preferred Qualifications
Experience with NVIDIA Quantum (InfiniBand) and Spectrum (Ethernet) switch architectures. Knowledge of POSIX, NFS over RDMA, and S3/Object storage protocols. Experience in data-heavy verticals (Finance/HFT, Life Sciences, Autonomous Research). Industry certifications such as NVIDIA Certified Associate/Professional (Networking) or equivalent. Certifications and Technical Skills
OpenShift and Kubernetes proficiency; knowledge of GPUDirect Storage (GDS) and RDMA-enabled data paths. EEO Statement
IBM is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, disability, neurodivergence, age, or other characteristics protected by applicable law. IBM is also committed to compliance with fair employment practices regarding citizenship and immigration status.
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