Lenovo wurde 1984 in einer Industriebaracke in Peking gegründet. Über die Jahre wurde das Unternehmen zum führenden PC-Hersteller Chinas und erwarb dann den PC-Geschäftsbereich von IBM, des ersten Personal-Computer-Herstellers.
Lenovo wurde 1984 in einer Industriebaracke in Peking gegründet. Über die Jahre wurde das Unternehmen zum führenden PC-Hersteller Chinas und erwarb dann den PC-Geschäftsbereich von IBM, des ersten Personal-Computer-Herstellers.
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Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY)
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit , and read about the latest news via our
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
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