Automation Manager Visa Sponsorship Jobs in North Carolina
Automation manager visa sponsorship jobs in North Carolina are concentrated in the Research Triangle, Charlotte, and the Piedmont Triad, where manufacturers like Siemens, Honeywell, and ABB operate alongside semiconductor and pharmaceutical facilities. The state's mix of advanced manufacturing, life sciences, and industrial automation creates consistent demand for experienced automation managers who need employer-sponsored visas.
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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
Automation Manager Job Roles in North Carolina
See all Automation Manager Jobs in North Carolina
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Search Automation Manager Jobs in North CarolinaAutomation Manager Jobs in North Carolina: Frequently Asked Questions
Which companies sponsor visas for automation managers in North Carolina?
North Carolina employers with documented H-1B visa and green card sponsorship history in engineering and automation roles include Siemens, Honeywell, ABB, Lenovo, and Wolfspeed. Life sciences manufacturers such as Novo Nordisk and Pfizer, which operate large facilities in the state, have also sponsored engineering management positions. Sponsorship patterns vary by facility size and project pipeline, so verifying LCA filing history for each employer is worth the effort before applying.
What visa types realistically fit automation manager roles in North Carolina?
Automation manager roles typically qualify as specialty occupations requiring a bachelor's degree in electrical engineering, mechanical engineering, or a closely related field, making H-1B the most common path. Employers file a Labor Condition Application with the Department of Labor, then petition USCIS. H-1B is subject to an annual cap and selection process. For candidates already in H-1B status, portability allows starting with a new employer once the new petition is filed. EB-2 and EB-3 employment-based green cards are available for longer-term sponsorship through the PERM labor certification process.
How to find automation manager visa sponsorship jobs in North Carolina?
Migrate Mate lists automation manager roles at North Carolina employers with verified visa sponsorship history, searchable by city and industry. Because sponsorship willingness is not always stated in job postings, using a platform that surfaces LCA filing history by employer and role saves significant research time. Focusing on the Research Triangle, Charlotte, and the Piedmont Triad tends to yield the highest concentration of relevant openings in manufacturing, semiconductor, and pharmaceutical automation.
Which cities in North Carolina have the most automation manager sponsorship jobs?
The Research Triangle area, covering Raleigh, Durham, and Chapel Hill, leads in automation manager opportunities due to its semiconductor fabs, pharmaceutical plants, and advanced manufacturing firms. Charlotte draws automation talent for its energy sector and large industrial operations. The Piedmont Triad, including Greensboro and Winston-Salem, supports automation managers in aerospace manufacturing and logistics automation. Smaller markets like Fayetteville and Wilmington see occasional openings tied to specific industrial facilities.
Are there state-specific factors that affect visa sponsorship for automation managers in North Carolina?
North Carolina's semiconductor expansion, anchored by Wolfspeed's Silicon Carbide facility in Durham and ongoing chip-sector investment, is creating sustained demand for automation engineering leadership. The state's pharmaceutical manufacturing base in the Research Triangle adds another sponsorship-active sector. NC State University and UNC produce engineering graduates who enter the local talent pool, but international candidates with specialized industrial automation experience, particularly in cleanroom, PLC, or SCADA systems, remain competitive for sponsored roles at established manufacturers.
What is the prevailing wage for sponsored automation manager 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.