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.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.