Cloud AI Architect Jobs in USA with Visa Sponsorship
Cloud AI Architect roles attract strong H-1B sponsorship from hyperscalers, enterprise software firms, and AI-native startups. The specialty occupation standard is straightforward for this title: employers consistently require a bachelor's degree or higher in computer science, engineering, or a related field. For detailed occupation requirements, see the O*NET profile.
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INTRODUCTION
We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 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.
Sr Engineer, Cloud AI Architect
Position Description
At Lenovo, we Never Stand Still. Every day, every employee at Lenovo is focused on moving forward, rejecting traditional limits, and always seeking a better way. We’re looking for a Cloud AI Architect within the Global Innovation Center (GIC) Group at Lenovo. In this role as an AI and Large Language Model Architect, you will play a pivotal role in designing and implementing the technology architecture for advanced AI (including Large Language Model (LLM)) platform systems and solutions. This role demands a skilled professional capable of designing and implementing advanced agentic AI systems that leverage both the Model Context Protocol (MCP) for contextual grounding and Agent-to-Agent (A2A) communication for seamless collaboration and task delegation between agents. You will translate business roadmap into technical requirements and architecture. Your contributions will be instrumental in shaping cutting-edge architectures, frameworks, and methodologies, pushing the boundaries of natural language processing (NLP) and machine learning. You will architect sophisticated large language models (LLMs) with the remarkable ability to process and generate natural language. Additionally, you will have the opportunity to design neural network parameters, leveraging extensive amounts of unlabeled text data, to further enhance the model's capabilities.
ROLE
- Produce high quality architecture specifically on AI, including LLMs, Inference Engineering and Prompt Engineering and design specifications.
- Experience finetuning an Opensource LLM.
- Architect and design end to end Generative AI products, applications and solutions for specific business needs and provide implementation guidance during delivery.
- Designing and implementing autonomous AI agents capable of reasoning, planning, acting, and adapting to achieve complex objectives.
- Integrating Large Language Models (LLMs) with memory, tool-use, and multi-step planning architectures, leveraging their natural language understanding and generation capabilities as the agent's "brain".
- Utilizing MCP servers or similar mechanisms to enable AI agents to interact with external enterprise applications, databases, and APIs.
- Designing and implementing agentic workflows where multiple agents communicate and collaborate using the A2A protocol to achieve shared goals.
- Analyze and evaluate the performance of Gen AI systems and provide design recommendations.
- Research, design, and implement machine learning models and algorithms, with a focus on LLM and Deep Learning techniques.
- Collaborate with cross-functional teams to identify business problems and opportunities where machine learning solutions can add value.
- Develop and deploy scalable and efficient machine learning pipelines for processing and analyzing large volumes of structured and unstructured data.
- Perform data preprocessing, feature engineering, and model training/validation using state-of-the-art machine learning frameworks and libraries.
- Evaluate model performance and interpret results to derive actionable insights and recommendations.
- Estimate cost of using LLMs in different forms for business use cases and the viability, develop cost models for different usage patterns.
- Design and prototype reusable components for LLM based solution patterns.
- Architect components of an LLM solution to address Responsible AI Security.
- Collaborate seamlessly with diverse, cross-functional teams to accurately identify and prioritize requirements, ensuring that the language model meets the needs and expectations of various stakeholders.
- Create and maintain comprehensive technical documentation that comprehensibly captures the intricate details of the language model, facilitating seamless understanding, efficient troubleshooting, and future development.
- Harness the power of transformer architecture, a cutting-edge deep learning model widely employed in natural language processing and computer vision, to optimize the language model's performance and efficiency.
BASIC QUALIFICATIONS
- Must be able to be onsite in Morrisville, North Carolina or able to relocate here.
- BA/BS degree in Computer Science or related software engineering field, or equivalent experience.
- Minimum of 6 years of experience in designing deploying AI / ML solutions using at least one cloud vendor.
- Minimum of 1 year of experience in the LLM and Generative AI space.
- Minimum of 1 year of experience architecting and operationalizing LLM driven application architecture patterns.
- 2+ Experience with specific AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, MLflow).
- Bachelor’s degree or equivalent work experience (minimum of 12 years), or an associate degree with a minimum of 6 years of equivalent work experience.
- Able to come into the office 3 days a week in Morrisville, North Carolina.
PREFERRED QUALIFICATIONS
- Deep understanding of AI/ML concepts, including LLMs, transformers, and prompt engineering.
- Experience with agentic AI frameworks such as LangChain, AutoGPT, Agentforce, LangGraph, or similar.
- Familiarity with the Model Context Protocol (MCP) standard and its role in providing context to AI agents.
- Experience with Agent-to-Agent (A2A) communication protocols and frameworks, enabling multi-agent collaboration and task delegation.
- Demonstrable experience implementing and maintaining globally distributed, highly redundant, scalable cloud-hosted solutions.
- Ability to demonstrate knowledge of a container technology such as Docker.
- Proficient technical knowledge of current tools and best practices at scale.
- Demonstrable experience working with distributed teams 3rd-party vendors.
- Experience with monitoring and logging cloud services and infrastructure.
- Experience using code management tooling such as Git/SVN/CVS.
- Significant experience working with Linux servers and command lines.
- Strong written and verbal communication skills.
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.

INTRODUCTION
We are Lenovo. We do what we say. We own what we do. We WOW our customers. Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 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.
Sr Engineer, Cloud AI Architect
Position Description
At Lenovo, we Never Stand Still. Every day, every employee at Lenovo is focused on moving forward, rejecting traditional limits, and always seeking a better way. We’re looking for a Cloud AI Architect within the Global Innovation Center (GIC) Group at Lenovo. In this role as an AI and Large Language Model Architect, you will play a pivotal role in designing and implementing the technology architecture for advanced AI (including Large Language Model (LLM)) platform systems and solutions. This role demands a skilled professional capable of designing and implementing advanced agentic AI systems that leverage both the Model Context Protocol (MCP) for contextual grounding and Agent-to-Agent (A2A) communication for seamless collaboration and task delegation between agents. You will translate business roadmap into technical requirements and architecture. Your contributions will be instrumental in shaping cutting-edge architectures, frameworks, and methodologies, pushing the boundaries of natural language processing (NLP) and machine learning. You will architect sophisticated large language models (LLMs) with the remarkable ability to process and generate natural language. Additionally, you will have the opportunity to design neural network parameters, leveraging extensive amounts of unlabeled text data, to further enhance the model's capabilities.
ROLE
- Produce high quality architecture specifically on AI, including LLMs, Inference Engineering and Prompt Engineering and design specifications.
- Experience finetuning an Opensource LLM.
- Architect and design end to end Generative AI products, applications and solutions for specific business needs and provide implementation guidance during delivery.
- Designing and implementing autonomous AI agents capable of reasoning, planning, acting, and adapting to achieve complex objectives.
- Integrating Large Language Models (LLMs) with memory, tool-use, and multi-step planning architectures, leveraging their natural language understanding and generation capabilities as the agent's "brain".
- Utilizing MCP servers or similar mechanisms to enable AI agents to interact with external enterprise applications, databases, and APIs.
- Designing and implementing agentic workflows where multiple agents communicate and collaborate using the A2A protocol to achieve shared goals.
- Analyze and evaluate the performance of Gen AI systems and provide design recommendations.
- Research, design, and implement machine learning models and algorithms, with a focus on LLM and Deep Learning techniques.
- Collaborate with cross-functional teams to identify business problems and opportunities where machine learning solutions can add value.
- Develop and deploy scalable and efficient machine learning pipelines for processing and analyzing large volumes of structured and unstructured data.
- Perform data preprocessing, feature engineering, and model training/validation using state-of-the-art machine learning frameworks and libraries.
- Evaluate model performance and interpret results to derive actionable insights and recommendations.
- Estimate cost of using LLMs in different forms for business use cases and the viability, develop cost models for different usage patterns.
- Design and prototype reusable components for LLM based solution patterns.
- Architect components of an LLM solution to address Responsible AI Security.
- Collaborate seamlessly with diverse, cross-functional teams to accurately identify and prioritize requirements, ensuring that the language model meets the needs and expectations of various stakeholders.
- Create and maintain comprehensive technical documentation that comprehensibly captures the intricate details of the language model, facilitating seamless understanding, efficient troubleshooting, and future development.
- Harness the power of transformer architecture, a cutting-edge deep learning model widely employed in natural language processing and computer vision, to optimize the language model's performance and efficiency.
BASIC QUALIFICATIONS
- Must be able to be onsite in Morrisville, North Carolina or able to relocate here.
- BA/BS degree in Computer Science or related software engineering field, or equivalent experience.
- Minimum of 6 years of experience in designing deploying AI / ML solutions using at least one cloud vendor.
- Minimum of 1 year of experience in the LLM and Generative AI space.
- Minimum of 1 year of experience architecting and operationalizing LLM driven application architecture patterns.
- 2+ Experience with specific AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, MLflow).
- Bachelor’s degree or equivalent work experience (minimum of 12 years), or an associate degree with a minimum of 6 years of equivalent work experience.
- Able to come into the office 3 days a week in Morrisville, North Carolina.
PREFERRED QUALIFICATIONS
- Deep understanding of AI/ML concepts, including LLMs, transformers, and prompt engineering.
- Experience with agentic AI frameworks such as LangChain, AutoGPT, Agentforce, LangGraph, or similar.
- Familiarity with the Model Context Protocol (MCP) standard and its role in providing context to AI agents.
- Experience with Agent-to-Agent (A2A) communication protocols and frameworks, enabling multi-agent collaboration and task delegation.
- Demonstrable experience implementing and maintaining globally distributed, highly redundant, scalable cloud-hosted solutions.
- Ability to demonstrate knowledge of a container technology such as Docker.
- Proficient technical knowledge of current tools and best practices at scale.
- Demonstrable experience working with distributed teams 3rd-party vendors.
- Experience with monitoring and logging cloud services and infrastructure.
- Experience using code management tooling such as Git/SVN/CVS.
- Significant experience working with Linux servers and command lines.
- Strong written and verbal communication skills.
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.
How to Get Visa Sponsorship in Cloud AI Architect
Target employers with established H-1B filing histories
Large cloud providers and enterprise software companies file hundreds of H-1B petitions annually for architecture roles. Prioritizing these employers significantly reduces the risk of a first-time sponsor struggling with USCIS requirements or petition preparation.
Align your degree field to your specialization
USCIS scrutinizes whether your degree matches the role. A computer science, information systems, or electrical engineering degree maps cleanly to Cloud AI Architect. A general business degree will require additional documentation linking coursework to the technical responsibilities.
Certifications strengthen your petition, not replace your degree
AWS Solutions Architect, Google Cloud Professional, and Azure certifications signal practical expertise to employers and can support your petition. They do not substitute for the degree requirement USCIS applies to specialty occupation determinations for this title.
Negotiate for premium processing from the start
Premium processing provides a 15-business-day adjudication window, which matters when you have a project start date or are transitioning between employers. Many tech companies cover this cost, but confirm it during offer negotiation rather than after signing.
Document your AI-specific responsibilities in detail
Generic job descriptions weaken H-1B petitions. Work with your employer to ensure the support letter specifies your cloud architecture deliverables, AI platform responsibilities, and the technical degree requirement, giving USCIS a clear specialty occupation case.
Understand your cap-exempt options if lottery selection fails
Universities, nonprofit research institutions, and certain government-affiliated organizations are cap-exempt H-1B employers. Cloud AI Architects are increasingly hired by these entities, offering a path to H-1B status outside the annual lottery entirely.
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Get Access To All JobsFrequently Asked Questions
Is Cloud AI Architect a strong H-1B specialty occupation?
Yes. Cloud AI Architect consistently qualifies as a specialty occupation because the role requires a bachelor's degree or higher in computer science, engineering, or a directly related technical field as a standard industry requirement. USCIS approval rates for software and cloud architecture titles are among the highest across all technical occupations, and the degree-to-role alignment is well established in the industry.
Which visa types do Cloud AI Architects typically use for U.S. work authorization?
The H-1B is the primary path for most applicants. Australians can use the E-3, which has no lottery and a significantly shorter sponsorship timeline. Canadians and Mexicans may qualify for TN status under the USMCA. Applicants with an exceptional portfolio of published research, patents, or industry recognition may also qualify for the O-1A, which has no cap and no lottery.
Does my degree field matter for sponsorship in this role?
It does. USCIS requires that the degree field directly relates to the job's technical duties. Computer science, software engineering, information systems, and electrical engineering are clean matches. If your degree is in a different field, your employer's attorney will need to document the connection through coursework, advanced certifications, or progressive experience. A mismatched degree isn't automatically disqualifying, but it adds complexity to the petition.
How can I find Cloud AI Architect roles where employers are open to sponsorship?
Migrate Mate filters job listings specifically for visa sponsorship eligibility, so you're not applying blindly to roles where sponsorship is unavailable. Cloud AI Architect positions on Migrate Mate come from employers who have indicated willingness to sponsor, which saves significant time compared to manually screening postings and contacting recruiters to confirm sponsorship availability before applying.
Can I switch employers on an H-1B as a Cloud AI Architect?
Yes, and it's one of the more flexible aspects of H-1B status. Your new employer files an H-1B transfer petition, and under portability rules you can begin work with the new employer as soon as the petition is filed, without waiting for approval. The transfer does not reset your priority date or require a new lottery selection, provided your original H-1B was properly approved and you've maintained valid status.
What is the prevailing wage requirement for sponsored Cloud AI Architect jobs?
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.
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