H-1B Visa Cluster Manager Jobs
Cluster Manager jobs with H-1B visa sponsorship sit at the intersection of operations leadership and technical coordination, typically requiring a bachelor's degree in business, engineering, computer science, or a related field. Employers filing LCAs for these roles span logistics, technology, and agriculture, making sponsorship more accessible than many candidates expect.
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Get Access To All JobsGENERAL INFORMATION
Req #
WD00108202
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Tuesday, November 3, 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
Job Title: Manager, AI Cluster Management & Automation
Job Type: Development Engineering Manager
Band: 8
Employment Type: Full-time
Location: Morrisville, NC
POSITION OVERVIEW
We are seeking an experienced engineering manager to lead the technical strategy, architecture, integration, and development of AI cluster management, deployment, validation, and automation software, leveraging open-source AI infrastructure as the software foundation.
This role focuses on bare-metal AI/HPC infrastructure deployment and lifecycle management, including physical server, GPU, networking, storage, and data center infrastructure bring-up, provisioning, validation, automation, and operational readiness. The successful candidate will lead development of scalable software and workflows that enable automated deployment, validation, monitoring, and lifecycle management of production AI clusters.
ACTOR is the cluster automation and validation software layer that integrates infrastructure components into end-to-end deployment, testing, certification, and lifecycle-management workflows. This role combines software architecture, AI/HPC infrastructure expertise, project delivery, and people leadership to build scalable, reliable cluster-deployment and validation solutions.
The manager will collaborate with solution architects, GPU/server engineering, networking, storage, data center infrastructure, services, customers, and technology partners including NVIDIA and AMD, while maintaining clear integration boundaries for AMD and other supported environments.
Important: This is a bare-metal AI infrastructure engineering leadership role. Successful candidates will have experience deploying, validating, automating, and operating physical GPU clusters, servers, networking, and storage infrastructure. Experience limited to provisioning cloud-based virtual infrastructure (AWS, Azure, GCP, or similar public-cloud environments) without significant bare-metal deployment and validation experience will generally not meet the requirements of this position.
KEY RESPONSIBILITIES:
1. Technical and Engineering Leadership
- Own the technical roadmap and software architecture for a cluster-validation solution built on open-source AI infrastructure, defining responsibilities across infrastructure components, ACTOR, and partner systems.
- Lead ACTOR development as an integration and workflow layer, prioritizing hardware enablement, deployment automation, validation, and customer-specific capabilities that complement the underlying open-source AI infrastructure.
- Lead software architecture and automation for bare-metal cluster deployment, hardware validation, infrastructure qualification, cluster bring-up, and acceptance testing supporting production-scale AI and HPC environments.
- Define modular, API-driven architectures spanning discovery, provisioning, configuration, observability, validation, and lifecycle management; make explicit reuse, integration, extension, and build decisions to avoid duplicating platform capabilities.
- Establish engineering standards, design reviews, automated integration testing, and release practices, including component compatibility, upgrade and rollback strategies, security, and upstream change management.
- Drive technical decisions around deployment repeatability, validation coverage, observability, operational resilience, and lifecycle-management automation for large-scale AI cluster environments.
2. Platform Integration
- Lead adoption and integration of selected open-source AI infrastructure components for infrastructure operations, accelerated Kubernetes, observability, security, health, and resilience; integrate NVIDIA Network Config and NICo where applicable to the deployment architecture.
- Maintain modular adapters for AMD cluster-management environments and other supported platforms, validating cross-vendor compatibility of selected open-source AI infrastructure components.
- Integrate Redfish, BMC, OpenBMC, and related management interfaces to support bare-metal server provisioning, hardware inventory discovery, firmware management, power control, diagnostics, cluster bring-up, and lifecycle operations.
- Integrate NetBox and data center infrastructure management (DCIM) systems.
- Integrate Ansible-based infrastructure automation.
- Integrate Kubernetes-based orchestration and selected GPU/network operators, defining clear ownership between infrastructure automation and workload platforms.
- Integrate Slurm and applicable GPU orchestration platforms and connect Prometheus/Grafana with platform telemetry rather than creating parallel scheduling or monitoring systems.
- Develop versioned integrations using REST APIs and infrastructure-management interfaces, with authentication, authorization, error handling, and compatibility testing.
- Design and automate end-to-end cluster deployment workflows spanning rack integration, hardware discovery, network configuration, operating system provisioning, GPU enablement, acceptance testing, validation, and operational handoff.
- Develop validation frameworks for physical AI infrastructure, including server qualification, GPU validation, networking verification, storage integration testing, cluster health assessment, deployment certification, and production-readiness testing.
- Connect cluster health monitoring, diagnostics, and telemetry to actionable validation and remediation workflows, with safe execution controls and clear operational handoffs.
3. Project & People Management
- Manage engineers delivering platform integration, cluster automation, networking, GPU operations, OS/platform software, and infrastructure management.
- Translate the roadmap into engineering priorities, integration milestones, and clear assignments, focusing custom development on differentiated capabilities.
- Lead project execution against program milestones and software release objectives, tracking deployment repeatability, integration quality, hardware-validation readiness, and validation coverage.
- Coordinate dependencies across internal engineering, solution teams, NVIDIA, AMD, and other partners, including platform changes, defect escalation, and support boundaries.
- Balance near-term customer commitments with a maintainable platform roadmap, reducing fragmented integrations and long-term upgrade burden.
- Lead engineering efforts supporting deployment readiness and validation of production AI clusters, ensuring repeatable, scalable, and automated installation, qualification, and certification processes across customer and data center environments.
- Develop and mentor engineering talent while fostering a culture of technical excellence, collaboration, accountability, and continuous improvement.
REQUIRED QUALIFICATIONS
-
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
-
8+ years of experience in software engineering, infrastructure engineering, cluster management, distributed systems, AI/HPC infrastructure, or related areas.
-
Experience leading technical projects and/or engineering teams.
-
Strong software architecture and system-design skills, including modular integration, API contracts, reuse-versus-build decisions, and component lifecycle management.
-
Hands-on experience deploying, managing, and troubleshooting Linux-based bare-metal infrastructure in AI, HPC, data center, or large-scale distributed computing environments.
-
Programming or scripting experience with one or more languages such as Python, Go, Rust, C/C++, Bash, or comparable languages.
-
Experience integrating infrastructure platforms through APIs and automation/configuration technologies such as Ansible, including automated testing, release management, and compatibility validation.
-
Strong knowledge in one or more of the following areas:
- AI/HPC cluster management
- Bare-metal infrastructure automation
- GPU cluster operations
- Infrastructure or network automation
- Data center infrastructure management (DCIM)
- Server provisioning and lifecycle management
-
Hardware validation and cluster qualification
-
Understanding of modern AI/HPC infrastructure including GPU compute, high-performance networking, storage, cluster management, and physical infrastructure deployment.
-
Experience designing, deploying, validating, or automating bare-metal AI, HPC, or data center infrastructure environments, including physical servers, GPU platforms, networking, storage, and cluster-management systems.
-
Experience with hardware provisioning, platform bring-up, firmware validation, infrastructure acceptance testing, deployment automation, or production infrastructure qualification processes.
-
Strong communication, technical leadership, and cross-functional collaboration skills.
PREFERRED QUALIFICATIONS
-
Experience with NVIDIA GPU infrastructure, HGX, DGX, NVL-class systems, AI factories, or AMD GPU clusters.
-
Familiarity with open-source AI infrastructure and modular software ecosystems, or hands-on experience with infrastructure and vendor components such as NVIDIA BCM, NICo, Mission Control, Kubernetes GPU/Network Operators, DCGM, or comparable cluster-management technologies.
-
Strong hands-on experience with Redfish, BMC/OpenBMC, PXE-based provisioning, MAAS, xCAT, Foreman, Ironic, Canonical MAAS, or similar bare-metal deployment and lifecycle-management technologies.
-
Experience with NetBox, DCIM, digital-twin platforms, infrastructure inventory systems, asset-management platforms, or topology-management solutions.
-
Understanding of InfiniBand, RoCE, Ethernet, and large-scale GPU-cluster networking.
-
Experience integrating or extending production-scale infrastructure-management, Kubernetes, Slurm, or GPU orchestration platforms, including multi-tenant isolation, observability, security, lifecycle management, and operational resilience.
-
Experience with MLPerf, NCCL testing, GPU diagnostics, burn-in testing, cluster acceptance testing, hardware qualification, platform certification, or deployment-validation frameworks.
-
Experience validating, deploying, or operating NVIDIA HGX, DGX, NVL platforms, AMD GPU clusters, HPC clusters, or large-scale accelerated-computing environments.
-
Experience working with hyperscalers, neocloud providers, cloud service providers (CSPs), enterprise customers, or large-scale data center operators.
-
Experience supporting rack-scale AI infrastructure deployment, cluster bring-up, server qualification, firmware validation, or production deployment certification activities.
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 #
WD00108202
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Tuesday, November 3, 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
Job Title: Manager, AI Cluster Management & Automation
Job Type: Development Engineering Manager
Band: 8
Employment Type: Full-time
Location: Morrisville, NC
POSITION OVERVIEW
We are seeking an experienced engineering manager to lead the technical strategy, architecture, integration, and development of AI cluster management, deployment, validation, and automation software, leveraging open-source AI infrastructure as the software foundation.
This role focuses on bare-metal AI/HPC infrastructure deployment and lifecycle management, including physical server, GPU, networking, storage, and data center infrastructure bring-up, provisioning, validation, automation, and operational readiness. The successful candidate will lead development of scalable software and workflows that enable automated deployment, validation, monitoring, and lifecycle management of production AI clusters.
ACTOR is the cluster automation and validation software layer that integrates infrastructure components into end-to-end deployment, testing, certification, and lifecycle-management workflows. This role combines software architecture, AI/HPC infrastructure expertise, project delivery, and people leadership to build scalable, reliable cluster-deployment and validation solutions.
The manager will collaborate with solution architects, GPU/server engineering, networking, storage, data center infrastructure, services, customers, and technology partners including NVIDIA and AMD, while maintaining clear integration boundaries for AMD and other supported environments.
Important: This is a bare-metal AI infrastructure engineering leadership role. Successful candidates will have experience deploying, validating, automating, and operating physical GPU clusters, servers, networking, and storage infrastructure. Experience limited to provisioning cloud-based virtual infrastructure (AWS, Azure, GCP, or similar public-cloud environments) without significant bare-metal deployment and validation experience will generally not meet the requirements of this position.
KEY RESPONSIBILITIES:
1. Technical and Engineering Leadership
- Own the technical roadmap and software architecture for a cluster-validation solution built on open-source AI infrastructure, defining responsibilities across infrastructure components, ACTOR, and partner systems.
- Lead ACTOR development as an integration and workflow layer, prioritizing hardware enablement, deployment automation, validation, and customer-specific capabilities that complement the underlying open-source AI infrastructure.
- Lead software architecture and automation for bare-metal cluster deployment, hardware validation, infrastructure qualification, cluster bring-up, and acceptance testing supporting production-scale AI and HPC environments.
- Define modular, API-driven architectures spanning discovery, provisioning, configuration, observability, validation, and lifecycle management; make explicit reuse, integration, extension, and build decisions to avoid duplicating platform capabilities.
- Establish engineering standards, design reviews, automated integration testing, and release practices, including component compatibility, upgrade and rollback strategies, security, and upstream change management.
- Drive technical decisions around deployment repeatability, validation coverage, observability, operational resilience, and lifecycle-management automation for large-scale AI cluster environments.
2. Platform Integration
- Lead adoption and integration of selected open-source AI infrastructure components for infrastructure operations, accelerated Kubernetes, observability, security, health, and resilience; integrate NVIDIA Network Config and NICo where applicable to the deployment architecture.
- Maintain modular adapters for AMD cluster-management environments and other supported platforms, validating cross-vendor compatibility of selected open-source AI infrastructure components.
- Integrate Redfish, BMC, OpenBMC, and related management interfaces to support bare-metal server provisioning, hardware inventory discovery, firmware management, power control, diagnostics, cluster bring-up, and lifecycle operations.
- Integrate NetBox and data center infrastructure management (DCIM) systems.
- Integrate Ansible-based infrastructure automation.
- Integrate Kubernetes-based orchestration and selected GPU/network operators, defining clear ownership between infrastructure automation and workload platforms.
- Integrate Slurm and applicable GPU orchestration platforms and connect Prometheus/Grafana with platform telemetry rather than creating parallel scheduling or monitoring systems.
- Develop versioned integrations using REST APIs and infrastructure-management interfaces, with authentication, authorization, error handling, and compatibility testing.
- Design and automate end-to-end cluster deployment workflows spanning rack integration, hardware discovery, network configuration, operating system provisioning, GPU enablement, acceptance testing, validation, and operational handoff.
- Develop validation frameworks for physical AI infrastructure, including server qualification, GPU validation, networking verification, storage integration testing, cluster health assessment, deployment certification, and production-readiness testing.
- Connect cluster health monitoring, diagnostics, and telemetry to actionable validation and remediation workflows, with safe execution controls and clear operational handoffs.
3. Project & People Management
- Manage engineers delivering platform integration, cluster automation, networking, GPU operations, OS/platform software, and infrastructure management.
- Translate the roadmap into engineering priorities, integration milestones, and clear assignments, focusing custom development on differentiated capabilities.
- Lead project execution against program milestones and software release objectives, tracking deployment repeatability, integration quality, hardware-validation readiness, and validation coverage.
- Coordinate dependencies across internal engineering, solution teams, NVIDIA, AMD, and other partners, including platform changes, defect escalation, and support boundaries.
- Balance near-term customer commitments with a maintainable platform roadmap, reducing fragmented integrations and long-term upgrade burden.
- Lead engineering efforts supporting deployment readiness and validation of production AI clusters, ensuring repeatable, scalable, and automated installation, qualification, and certification processes across customer and data center environments.
- Develop and mentor engineering talent while fostering a culture of technical excellence, collaboration, accountability, and continuous improvement.
REQUIRED QUALIFICATIONS
-
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field.
-
8+ years of experience in software engineering, infrastructure engineering, cluster management, distributed systems, AI/HPC infrastructure, or related areas.
-
Experience leading technical projects and/or engineering teams.
-
Strong software architecture and system-design skills, including modular integration, API contracts, reuse-versus-build decisions, and component lifecycle management.
-
Hands-on experience deploying, managing, and troubleshooting Linux-based bare-metal infrastructure in AI, HPC, data center, or large-scale distributed computing environments.
-
Programming or scripting experience with one or more languages such as Python, Go, Rust, C/C++, Bash, or comparable languages.
-
Experience integrating infrastructure platforms through APIs and automation/configuration technologies such as Ansible, including automated testing, release management, and compatibility validation.
-
Strong knowledge in one or more of the following areas:
- AI/HPC cluster management
- Bare-metal infrastructure automation
- GPU cluster operations
- Infrastructure or network automation
- Data center infrastructure management (DCIM)
- Server provisioning and lifecycle management
-
Hardware validation and cluster qualification
-
Understanding of modern AI/HPC infrastructure including GPU compute, high-performance networking, storage, cluster management, and physical infrastructure deployment.
-
Experience designing, deploying, validating, or automating bare-metal AI, HPC, or data center infrastructure environments, including physical servers, GPU platforms, networking, storage, and cluster-management systems.
-
Experience with hardware provisioning, platform bring-up, firmware validation, infrastructure acceptance testing, deployment automation, or production infrastructure qualification processes.
-
Strong communication, technical leadership, and cross-functional collaboration skills.
PREFERRED QUALIFICATIONS
-
Experience with NVIDIA GPU infrastructure, HGX, DGX, NVL-class systems, AI factories, or AMD GPU clusters.
-
Familiarity with open-source AI infrastructure and modular software ecosystems, or hands-on experience with infrastructure and vendor components such as NVIDIA BCM, NICo, Mission Control, Kubernetes GPU/Network Operators, DCGM, or comparable cluster-management technologies.
-
Strong hands-on experience with Redfish, BMC/OpenBMC, PXE-based provisioning, MAAS, xCAT, Foreman, Ironic, Canonical MAAS, or similar bare-metal deployment and lifecycle-management technologies.
-
Experience with NetBox, DCIM, digital-twin platforms, infrastructure inventory systems, asset-management platforms, or topology-management solutions.
-
Understanding of InfiniBand, RoCE, Ethernet, and large-scale GPU-cluster networking.
-
Experience integrating or extending production-scale infrastructure-management, Kubernetes, Slurm, or GPU orchestration platforms, including multi-tenant isolation, observability, security, lifecycle management, and operational resilience.
-
Experience with MLPerf, NCCL testing, GPU diagnostics, burn-in testing, cluster acceptance testing, hardware qualification, platform certification, or deployment-validation frameworks.
-
Experience validating, deploying, or operating NVIDIA HGX, DGX, NVL platforms, AMD GPU clusters, HPC clusters, or large-scale accelerated-computing environments.
-
Experience working with hyperscalers, neocloud providers, cloud service providers (CSPs), enterprise customers, or large-scale data center operators.
-
Experience supporting rack-scale AI infrastructure deployment, cluster bring-up, server qualification, firmware validation, or production deployment certification activities.
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
See all H-1B Visa Cluster Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Cluster Manager Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Cluster Manager
Map your degree to specialty occupation
USCIS evaluates whether your specific degree field directly relates to Cluster Manager duties. Pull the O*NET occupation profile for your target job code and document how your coursework maps to the role's core functions before applying.
Search LCA filings by job title
Use the OFLC Wage Search to look up certified LCAs under titles like Cluster Manager, Operations Manager, or related SOC codes. Employers with recent certifications are actively sponsoring, which cuts your research time significantly.
Find sponsors through Migrate Mate
Filter Migrate Mate's job board by Cluster Manager roles to surface employers with verified H-1B LCA filing history. This shows you which companies have already committed to the sponsorship process for this type of position.
Clarify multi-site LCA coverage early
Cluster Manager roles often span multiple facilities or regions. Each worksite requires its own certified LCA from DOL, so confirm with your prospective employer that all locations where you'll regularly work are covered before you sign an offer.
Request premium processing before cap selection
If you're on OPT and facing a gap before H-1B status begins, ask your employer to include premium processing in the petition. USCIS adjudicates premium cases faster, reducing uncertainty if your start date is time-sensitive.
Document operational scope to satisfy specialty occupation
Cluster Manager petitions face scrutiny when job descriptions emphasize physical coordination over analytical decision-making. Work with your employer to frame the role around degree-level duties like supply chain modeling, performance analysis, or systems oversight.
H-1B Visa Cluster Manager: Frequently Asked Questions
Does a Cluster Manager role qualify as a specialty occupation for H-1B purposes?
Yes, Cluster Manager roles typically qualify when the position requires at least a bachelor's degree in a directly related field such as business administration, industrial engineering, supply chain management, or computer science. The employer must demonstrate in the I-129 petition that the duties demand theoretical and practical application of that specific body of knowledge, not just general management experience.
How do I find employers who sponsor H-1B visas for Cluster Manager positions?
Start with Migrate Mate, which lists employers with verified H-1B LCA filing history for operations and management roles. You can also cross-reference the OFLC Wage Search using relevant SOC codes to identify companies that have recently had LCAs certified for Cluster Manager or comparable titles, confirming active sponsorship intent.
What prevailing wage level should I expect a Cluster Manager LCA to target?
DOL assigns prevailing wages across four levels based on experience, supervision, and complexity. Cluster Manager roles that involve overseeing multiple teams or facilities typically land at Level II or III. Use the OFLC Wage Search with your target metro area and SOC code to see the specific wage floor your employer must certify before filing your LCA.
What happens to my H-1B status if the cluster I manage is restructured or relocated?
A material change to your worksite location or job duties requires your employer to file an amended H-1B petition with USCIS and obtain a new certified LCA for any new worksite. If the restructuring moves you to a location not covered by your existing LCA, you cannot work there until the amended petition is approved. Confirm coverage with your employer before any transfer takes effect.
How long does H-1B status last for a Cluster Manager, and can it be extended?
H-1B status is initially granted for up to three years and can be extended to a six-year maximum. Extensions beyond six years are possible only if your employer has filed a PERM labor certification or an I-140 immigrant petition on your behalf and specific milestones under AC21 have been met. Coordinate with your employer's immigration counsel well before the six-year cap approaches.