Solution Engineer Visa Sponsorship Jobs in North Carolina
Solution engineer roles in North Carolina are concentrated in the Research Triangle, where companies like Cisco, Red Hat, and SAS Institute regularly hire technical presales talent. Charlotte's growing fintech and banking sector adds another hiring corridor. International candidates pursuing visa sponsorship will find the state's deep enterprise software presence a strong foundation for their search.
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Get Access To All JobsGENERAL INFORMATION
Req #
WD00106394
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Monday, October 26, 2026
Working time:
Full-time
ADDITIONAL LOCATIONS
* United States of America - North Carolina - Morrisville
WHY WORK AT LENOVO
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
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 www.lenovo.com, and read about the latest news via our StoryHub.
DESCRIPTION AND REQUIREMENTS
Cluster Solution Architect
ABOUT OUR TEAM
Lenovo's Cloud Service Provider (CSP) team designs AI infrastructure solutions for hyperscalers, NeoCloud providers, and other data center customers. We bring together GPU platforms, high-performance networking, cluster software, and data center infrastructure to support large-scale AI training and inference.
As a Cluster Solutions Architect, you'll translate customer requirements into integrated, scalable solutions and compelling technical proposals. You'll collaborate with customers, sales teams, technology partners, and engineering teams to shape architectures that balance performance, efficiency, operational requirements, and deployment feasibility.
Ideal candidates will bring experience designing, architecting, and supporting large-scale AI infrastructure solutions in customer-facing environments, including GPU cluster deployments, AI inference platforms, and integrated hardware and software solutions for enterprise, cloud, hyperscale, or data center customers.
- Design and optimize end-to-end AI inference and AI training solutions, with a primary emphasis on AI inference architecture, software stack integration, and production deployment of large-scale GPU cluster environments using NVIDIA software and platform technologies, including NVIDIA AI Enterprise, Dynamo, NIM, NVIDIA Infrastructure Controller (NICo), Mission Control, LPx, and emerging inference acceleration capabilities.
- Evaluate architecture tradeoffs to improve token latency, throughput, GPU utilization, and overall AI service efficiency.
- Translate customer workload, capacity, networking, power, and cooling requirements into integrated cluster architectures and technical recommendations.
- Design integrated AI cluster solutions that combine GPU compute platforms, high-performance networking, software stack components, storage, and supporting data center infrastructure into scalable customer-ready architectures.
- Provide technical leadership and architecture guidance throughout the customer solution lifecycle, including requirements gathering, solution design, technical reviews, proposal development, and customer presentations.
- Develop and deliver technical presentations, proofs of concept (POCs), demonstrations, and customer-facing solution proposals that clearly articulate architecture decisions, business value, technical differentiation, and deployment considerations.
- Support customer engagements by evaluating technical requirements and recommending scalable AI cluster architectures that balance performance, operational efficiency, deployment feasibility, and cost considerations.
- Prepare and contribute to requests for proposal (RFPs) and requests for quotation (RFQs), including technical compliance responses, solution documentation, bills of materials (BOMs), and customer-facing architecture content.
- Partner with engineering, deployment, hardware, networking, and supply chain teams to validate proposed solutions and confirm technical feasibility.
- Mentor junior RFP contributors and sales engineers, providing guidance on customer requirements, solution design, and common architecture tradeoffs.
- Develop best practices, reusable templates, reference architectures, sizing guidelines, and technical response content to improve proposal quality and response speed.
- Stay current on GPU roadmaps, high-speed networking, liquid cooling, cluster management, AI software ecosystems, inference optimization technologies, and emerging data center technologies.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related engineering field; candidates with other educational backgrounds will also be considered if they demonstrate sufficient relevant technical knowledge.
- 10+ years of experience in data center infrastructure, solution architecture, systems engineering, pre-sales engineering, or technical consulting.
- Experience with large-scale AI inference and AI training workloads, including large language model (LLM) infrastructure, model serving environments, capacity planning, performance optimization, and production deployment of AI solutions.
- Experience designing, supporting, or deploying customer-facing AI infrastructure solutions, GPU clusters, high-performance computing environments, or large-scale data center architectures.
- Strong understanding of AI software stacks, cluster management environments, and infrastructure integration, with the ability to translate customer business and technical requirements into deployable solutions.
- Experience working directly with customers, technical stakeholders, sales teams, or solution engineering organizations to develop and validate technical solution designs.
- Strong knowledge of high-performance networking for AI clusters, including InfiniBand, RDMA over Converged Ethernet (RoCE), network operating systems, and deployment and discovery protocols such as ZTP, DHCP, LLDP, and SNMP.
- Familiarity with data center networking, high-speed optical interconnects, transceiver and fiber form factors, and interoperability requirements.
- Knowledge of liquid cooling, coolant distribution units (CDUs), high-density rack design, power distribution units (PDUs), busway systems, and AI data center power and cooling constraints.
- Familiarity with Python or another scripting language, automation tools, and infrastructure as code to support solution validation and design.
- Willingness to travel up to 10% for customer meetings, technical workshops, partner engagements, and industry events.
- Commitment to continuously learning new GPU, networking, and data center technologies.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related engineering field.
- 5+ years of experience preparing or contributing to RFP/RFQ responses, including technical compliance, solution documentation, BOM development, and customer-facing architecture content, ideally for NVIDIA HGX or DGX platforms.
- Working knowledge of cluster software and management environments, including Linux, Slurm, Kubernetes, Docker, NVIDIA Infrastructure Controller (NICo), NVIDIA Mission Control, ROCm, or related tools, with experience deploying and managing production AI inference environments preferred.
- Deep understanding of modern GPU server architectures, including NVIDIA and/or AMD accelerator-based systems.
- Experience supporting organizations that design, manufacture, integrate, or deploy enterprise AI infrastructure, GPU-based computing platforms, high-performance computing environments, or large-scale data center solutions.
- Familiarity with hyperscaler data center infrastructure and operating environments, with demonstrated experience supporting hyperscaler, NeoCloud, or other data center infrastructure customers.
- Demonstrated experience developing technical proposals, architecture documentation, statements of work, solution recommendations, or customer-facing technical deliverables for complex infrastructure projects.
- Strong written communication skills, with the ability to translate complex technical requirements into clear, accurate customer-facing proposals and architecture documentation.
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.
ADDITIONAL LOCATIONS
United States of America - North Carolina - Morrisville
United States of America
United States of America - North Carolina
United States of America - North Carolina - Morrisville
GENERAL INFORMATION
Req #
WD00106394
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Monday, October 26, 2026
Working time:
Full-time
ADDITIONAL LOCATIONS
* United States of America - North Carolina - Morrisville
WHY WORK AT LENOVO
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
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 www.lenovo.com, and read about the latest news via our StoryHub.
DESCRIPTION AND REQUIREMENTS
Cluster Solution Architect
ABOUT OUR TEAM
Lenovo's Cloud Service Provider (CSP) team designs AI infrastructure solutions for hyperscalers, NeoCloud providers, and other data center customers. We bring together GPU platforms, high-performance networking, cluster software, and data center infrastructure to support large-scale AI training and inference.
As a Cluster Solutions Architect, you'll translate customer requirements into integrated, scalable solutions and compelling technical proposals. You'll collaborate with customers, sales teams, technology partners, and engineering teams to shape architectures that balance performance, efficiency, operational requirements, and deployment feasibility.
Ideal candidates will bring experience designing, architecting, and supporting large-scale AI infrastructure solutions in customer-facing environments, including GPU cluster deployments, AI inference platforms, and integrated hardware and software solutions for enterprise, cloud, hyperscale, or data center customers.
- Design and optimize end-to-end AI inference and AI training solutions, with a primary emphasis on AI inference architecture, software stack integration, and production deployment of large-scale GPU cluster environments using NVIDIA software and platform technologies, including NVIDIA AI Enterprise, Dynamo, NIM, NVIDIA Infrastructure Controller (NICo), Mission Control, LPx, and emerging inference acceleration capabilities.
- Evaluate architecture tradeoffs to improve token latency, throughput, GPU utilization, and overall AI service efficiency.
- Translate customer workload, capacity, networking, power, and cooling requirements into integrated cluster architectures and technical recommendations.
- Design integrated AI cluster solutions that combine GPU compute platforms, high-performance networking, software stack components, storage, and supporting data center infrastructure into scalable customer-ready architectures.
- Provide technical leadership and architecture guidance throughout the customer solution lifecycle, including requirements gathering, solution design, technical reviews, proposal development, and customer presentations.
- Develop and deliver technical presentations, proofs of concept (POCs), demonstrations, and customer-facing solution proposals that clearly articulate architecture decisions, business value, technical differentiation, and deployment considerations.
- Support customer engagements by evaluating technical requirements and recommending scalable AI cluster architectures that balance performance, operational efficiency, deployment feasibility, and cost considerations.
- Prepare and contribute to requests for proposal (RFPs) and requests for quotation (RFQs), including technical compliance responses, solution documentation, bills of materials (BOMs), and customer-facing architecture content.
- Partner with engineering, deployment, hardware, networking, and supply chain teams to validate proposed solutions and confirm technical feasibility.
- Mentor junior RFP contributors and sales engineers, providing guidance on customer requirements, solution design, and common architecture tradeoffs.
- Develop best practices, reusable templates, reference architectures, sizing guidelines, and technical response content to improve proposal quality and response speed.
- Stay current on GPU roadmaps, high-speed networking, liquid cooling, cluster management, AI software ecosystems, inference optimization technologies, and emerging data center technologies.
BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related engineering field; candidates with other educational backgrounds will also be considered if they demonstrate sufficient relevant technical knowledge.
- 10+ years of experience in data center infrastructure, solution architecture, systems engineering, pre-sales engineering, or technical consulting.
- Experience with large-scale AI inference and AI training workloads, including large language model (LLM) infrastructure, model serving environments, capacity planning, performance optimization, and production deployment of AI solutions.
- Experience designing, supporting, or deploying customer-facing AI infrastructure solutions, GPU clusters, high-performance computing environments, or large-scale data center architectures.
- Strong understanding of AI software stacks, cluster management environments, and infrastructure integration, with the ability to translate customer business and technical requirements into deployable solutions.
- Experience working directly with customers, technical stakeholders, sales teams, or solution engineering organizations to develop and validate technical solution designs.
- Strong knowledge of high-performance networking for AI clusters, including InfiniBand, RDMA over Converged Ethernet (RoCE), network operating systems, and deployment and discovery protocols such as ZTP, DHCP, LLDP, and SNMP.
- Familiarity with data center networking, high-speed optical interconnects, transceiver and fiber form factors, and interoperability requirements.
- Knowledge of liquid cooling, coolant distribution units (CDUs), high-density rack design, power distribution units (PDUs), busway systems, and AI data center power and cooling constraints.
- Familiarity with Python or another scripting language, automation tools, and infrastructure as code to support solution validation and design.
- Willingness to travel up to 10% for customer meetings, technical workshops, partner engagements, and industry events.
- Commitment to continuously learning new GPU, networking, and data center technologies.
PREFERRED QUALIFICATIONS
- Master's degree or PhD in Computer Science, Computer Engineering, Electrical Engineering, or a related engineering field.
- 5+ years of experience preparing or contributing to RFP/RFQ responses, including technical compliance, solution documentation, BOM development, and customer-facing architecture content, ideally for NVIDIA HGX or DGX platforms.
- Working knowledge of cluster software and management environments, including Linux, Slurm, Kubernetes, Docker, NVIDIA Infrastructure Controller (NICo), NVIDIA Mission Control, ROCm, or related tools, with experience deploying and managing production AI inference environments preferred.
- Deep understanding of modern GPU server architectures, including NVIDIA and/or AMD accelerator-based systems.
- Experience supporting organizations that design, manufacture, integrate, or deploy enterprise AI infrastructure, GPU-based computing platforms, high-performance computing environments, or large-scale data center solutions.
- Familiarity with hyperscaler data center infrastructure and operating environments, with demonstrated experience supporting hyperscaler, NeoCloud, or other data center infrastructure customers.
- Demonstrated experience developing technical proposals, architecture documentation, statements of work, solution recommendations, or customer-facing technical deliverables for complex infrastructure projects.
- Strong written communication skills, with the ability to translate complex technical requirements into clear, accurate customer-facing proposals and architecture documentation.
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.
ADDITIONAL LOCATIONS
United States of America - North Carolina - Morrisville
United States of America
United States of America - North Carolina
United States of America - North Carolina - Morrisville
Solution Engineer Job Roles in North Carolina
See all Solution Engineer Jobs in North Carolina
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Search Solution Engineer Jobs in North CarolinaSolution Engineer Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for solution engineers in North Carolina?
Enterprise technology companies in the Research Triangle are among the most active sponsors for solution engineer roles. Red Hat in Raleigh, Cisco in Research Triangle Park, and SAS Institute in Cary have established sponsorship histories for technical presales positions. Charlotte-based financial institutions like Bank of America and Wells Fargo also sponsor solution engineers supporting their technology divisions, particularly in cloud infrastructure and data platforms.
Which visa types are most common for solution engineer roles in North Carolina?
The H-1B visa is the most common visa category for solution engineers in North Carolina, as the role typically requires a bachelor's degree in computer science, engineering, or a related field, meeting specialty occupation criteria. Candidates from Australia may qualify for the E-3 visa. Canadian and Mexican nationals can explore the TN visa under the NAFTA/USMCA engineer category, provided their role aligns with the approved occupation list.
Which cities in North Carolina have the most solution engineer sponsorship jobs?
Raleigh and the broader Research Triangle Park area, which includes Durham and Cary, account for the largest share of solution engineer sponsorship jobs in North Carolina. This corridor hosts major enterprise software and cloud vendors. Charlotte is the second-largest hub, driven by its financial services sector and the technology firms that support it. Smaller pockets of activity exist in Greensboro and Charlotte's suburbs.
How to find solution engineer visa sponsorship jobs in North Carolina?
Migrate Mate is built specifically for international candidates and filters job listings by visa sponsorship availability, making it straightforward to search for solution engineer roles in North Carolina without sorting through positions that don't offer sponsorship. The platform covers enterprise software, fintech, and cloud vendors active in the Research Triangle and Charlotte markets, which are the two primary hiring corridors for this role in the state.
What should international candidates know about solution engineer hiring in North Carolina?
Solution engineer roles in North Carolina tend to require demonstrated technical depth in specific platforms, often cloud or data infrastructure, alongside presales experience. Employers filing H-1B petitions must pay the Department of Labor prevailing wage for the relevant occupation and geographic area. The Research Triangle's concentration of university graduates from NC State, Duke, and UNC creates a competitive local talent pool, so international candidates benefit from highlighting platform certifications and client-facing experience.
What is the prevailing wage for sponsored solution engineer jobs in North Carolina?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.