Neo-Cloud Solutions Architect (with Data Center experience)

• Position : Neo-Cloud Solutions Architect (with Data Center experience)
• Location : Remote

• Must have: data center design, development, and execution for AI and HPC
• .We're seeking an experienced Solutions Architect to bridge the gap between design and deployment of large-scale AI and HPC GPU infrastructure. This role serves as the primary technical point of contact for the customer throughout the full lifecycle of building next-generation GPU cloud infrastructure — driving end-to-end technology solution integration and sharing field feedback with business and engineering teams to help shape product strategy
• .Key Responsibilities
• :Collaborate with the customer's cloud partners to design, implement, and operationalize innovative GPU hardware and software solutions
• .Partner with Sales Account Managers and other business leads to identify and secure business opportunities for GPU infrastructure products and solutions
• .Act as the primary technical point of contact for the customer through the full lifecycle of developing, building, and bringing large-scale GPU cloud infrastructure into production
• .Lead regular technical customer meetings covering project and product details, feature discussions, introductions to new technologies, and debugging sessions
• .Work with the customer to build proofs of concept addressing critical business needs across networking and compute infrastructure
• .Prepare and deliver technical content to the customer, including presentations and workshops
• .Analyze and develop joint solutions for customer performance and scaling issues
• .Required Qualifications
• :Motivation and skill to own and drive technical engagements with customers across the full customer lifecycle
• .7+ years of Solution Engineering (or similar Sales Engineering / Cloud Engineering) experience working directly with partners and customers
• .Experience crafting and deploying large-scale cluster environments
• .Practical expertise in data center design, development, and execution for AI and HPC
• .Strong time management skills and the ability to balance multiple tasks, with clear communication through documents and presentations
• .Nice to Have
• :Practical familiarity with GPU hardware and networking components (Ethernet/InfiniBand), storage, and other elements of large-scale AI and HPC cluster environments
• .Practical knowledge of GPU systems management technologies such as NCCL, DCGM, UFM, Mission Control, and Base Command Manager
• .Background with at-scale GPU systems, including performance testing and AI benchmarking
• .Hands-on experience with cluster administration and orchestration (SLURM, Kubernetes)

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