Cluster Solution Architect

Key Responsibilities:

• Lead technical ownership of customer RFP, RFQ, and responses for AI and HPC GPU cluster opportunities. Design AI cluster solutions based on the latest NVIDIA and AMD GPU hardware platforms.
• Analyze customer requirements and develop complete cluster solutions including compute, networking, storage, power, cooling, rack/datacenter layout, and management software during the pre-sales and RFP process.
• Design and deliver compelling technical presentations, POC, or demos that clearly articulate Lenovo's competitiveness in customer use cases.
• Mentor and provide technical leadership to junior RFP participants and sales engineers on solutions, customer requirements, and common architecture tradeoffs.
• Work with internal engineering, deployment, hardware, networking, and supply chain teams to validate proposed solutions and ensure they are technically feasible.
• Develop best practices, reusable templates, reference architectures, sizing guidelines, and RFP response content to improve proposal quality and response speed.
• Stay current on AI infrastructure trends, including GPU roadmap changes, high-speed networking, liquid cooling, cluster management, and AI software ecosystems.

Required Qualifications:

• BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or other related engineering fields. Individuals with other backgrounds will also be considered if sufficient knowledge demonstrated in the topics listed below.
• 10+ years of experience in data center infrastructure, solution architecture, systems engineering, pre-sales engineering, or technical consulting.
• Familiarity with Python or other scripting language and automation tools, and infrastructure-as-code for solution validation or design support.
• Familiarity with datacenter networking, high-speed optical interconnections, transceiver and fiber form factors, and their respective interoperability models.
• Strong knowledge of high-performance networking for AI clusters, such as InfiniBand, RoCE, networking operating systems, and common Day 0/Day 1 networking protocols (ZTP, DHCP, LLDP, SNMP, etc.)
• Knowledge of liquid cooling, CDU, high-density rack design, PDU, busway, and modern AI data center power/cooling constraints.
• Experience with large scale AI training and inference workloads, including LLM infrastructure pipeline and capacity planning.
• Willingness to travel up to 10% for customer meetings, technical workshops, partner engagements, and industry events.
• Willingness to continuously learn new GPU, networking, and data center technologies.

Preferred Qualifications:

• MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or other related engineering fields
• 5+ years of experience preparing or contributing to RFP/RFQ responses, including technical compliance, solution documentation, BOM development, and customer-facing architecture content, ideally on NVIDIA HGX or DGX platforms.
• Working knowledge of cluster software and management environments such as Linux, Slurm, Kubernetes, Docker, NVIDIA Infrastructure Controller (NICo), NVIDIA Mission Control, ROCm, or related tools.
• Deep understanding of modern GPU server architectures, including NVIDIA and/or AMD accelerator-based systems.
• Familiarity with hyperscaler datacenter and operation environment. Proven experience in working with hyperscaler/NeoCloud/ other datacenter infrastructure or customers.
• Strong written communication skills for creating clear customer-facing technical responses