H-1B Visa AI Data Specialist Jobs
AI Data Specialist roles qualify as H-1B visa specialty occupations under the computer and mathematical occupations category, requiring at least a bachelor's degree in computer science, data science, statistics, or a directly related field. Employers filing H-1B petitions for this role must certify a prevailing wage through DOL before USCIS adjudicates the petition.
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GENERAL INFORMATION
Req #
WD00099074
Career area:
Artificial Intelligence
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Wednesday, May 27, 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 #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices; and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world-class innovation and a full-stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
DESCRIPTION AND REQUIREMENTS
As an AI Data Specialist, you will play a key role in the design, development, and deployment of an Agentic AI platform that streamlines the creation of AI-driven customer solutions. You will work closely with AI engineers and cross-functional teams to support the deployment, integration, and scaling of AI services across enterprise environments. In this role, you will leverage your expertise in data management, AI technologies, and development practices to build efficient, reusable, and scalable data-driven solutions. You will be responsible for ensuring that data pipelines, models, and AI components are effectively integrated into a cohesive and high-performing platform. To succeed, you should possess a strong understanding of AI and data ecosystems, demonstrate hands-on technical skills, and have the ability to transform complex data and AI tools into standardized, repeatable solutions that drive business value.
This role sits within Lenovo’s Solutions & Services Group (SSG), the global organization that brings together our end-to-end AI solutions and services to turn customer vision into value. You’ll be joining a new, distributed engineering team building the xIQ Agent Platform, an AI-native delivery platform that powers Lenovo’s Agentic AI strategy across hybrid cloud, on-prem, and edge.
- Design, develop, and implement data-driven AI solutions for an Agentic AI platform, aligning with enterprise architecture and business objectives.
- Build and maintain scalable data processing pipelines for AI workloads, including data ingestion, cleansing, transformation, and feature engineering.
- Develop and deploy end-to-end AI systems using LLMs, SLMs, and VLMs for advanced data processing, enrichment, and automation.
- Leverage NVIDIA AI technologies (e.g., CUDA, NV-Ingest, VLM..etc) or similar platforms to optimize model training, fine-tuning, and inference performance.
- Implement and manage vector databases such as Milvus, PostgreSQL (PGVector), or other vector stores to support semantic search, embeddings, and Retrieval-Augmented Generation (RAG) use cases.
- Design and optimize data and retrieval pipelines that integrate structured and unstructured data with LLM-based reasoning systems.
- Develop and integrate AI components (APIs, microservices, inference layers) into enterprise platforms across cloud, on-premise, and edge environments.
- Select and implement data engineering and pipeline orchestration tools to ensure scalable and reliable data workflows.
- Apply best practices in data engineering, MLOps, and AIOps, including pipeline monitoring, versioning, and performance tuning.
- Ensure data security, governance, and compliance, including encryption, access control, and secure data handling practices.
- Write clean, maintainable, and reusable code following enterprise development standards and best practices.
- Create detailed technical documentation, including data flow architectures, pipeline designs, model integration patterns, and system interfaces.
- Continuously evaluate and adopt emerging AI, LLM, and data technologies to improve solution effectiveness and scalability.
- Support solution design discussions, PoCs, and pre-sales activities by providing expertise in AI data architecture and implementation.
- Effectively communicate technical designs, data strategies, and AI solutions to both technical teams and business stakeholders.
BASIC QUALIFICATIONS:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- 3-5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
PREFERRED QUALIFICATIONS:
- 2+ years of hands-on experience in building end-to-end Generative AI and data-driven solutions, including data preprocessing, embedding generation, and Retrieval-Augmented Generation (RAG) pipelines using LLMs and multimodal models (e.g., OpenAI, Anthropic, Llama, Hugging Face, Amazon Bedrock).
- Strong experience with data processing frameworks and pipeline development.
- Hands-on experience with vector databases such as Milvus, PostgreSQL (PGVector), Pinecone, or similar, including embedding management and semantic search implementations.
- Experience working with the NVIDIA AI ecosystem (e.g., GPUs, CUDA, TensorRT, NeMo) or equivalent acceleration technologies for efficient data processing, model training, and inference is a strong plus.
- Strong understanding of data architectures involving structured, semi-structured, and unstructured data, and building scalable pipelines to support AI/ML workloads.
- Experience integrating AI/data solutions across cloud and on-premise environments, including containerization and orchestration using Docker and Kubernetes.
- Proven experience implementing MLOps, LLMOps, and DataOps practices, including CI/CD pipelines, data versioning, monitoring, and lifecycle management using tools such as Jenkins, GitLab, MLflow, or similar.
- Strong programming skills in Python, with experience in data processing libraries (e.g., Pandas, PySpark), and familiarity with API development.
- Solid understanding of data governance, security, and compliance, including handling sensitive data and implementing access controls and encryption.
- Strong problem-solving skills and ability to translate complex data and AI requirements into scalable, reusable solutions.
This role offers the flexibility to be home-based anywhere in the U.S. with preference for the Eastern time zone. If you're near our Raleigh office, we follow a friendly hybrid model with three days a week in the office—great for collaboration and connection!
The base salary range budgeted for this position is $140,000 to $170,000. Individuals may also be considered for bonuses and/or commissions. Lenovo’s various benefits can be found at www.lenovobenefits.com
In compliance with Colorado's EPEWA, the expected Application Deadline for this position is 7/1/2026 - this applies to both internal and external candidates.
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 60+ H-1B Visa AI Data Specialist Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Data Specialist
Align your degree to the role
USCIS requires your degree field to directly relate to AI Data Specialist duties. If your degree is in a adjacent field like mathematics or information systems, prepare a credential evaluation showing how your coursework maps to data science and machine learning competencies.
Check prevailing wages before negotiating
Use the OFLC Wage Search to look up Level I through Level IV wages for your target job title and work location before you receive an offer. Your certified LCA wage sets a floor the employer cannot go below.
Target employers with active LCA filing history
Search for AI Data Specialist roles on Migrate Mate, which surfaces employers based on verified DOL Labor Condition Application data so you can see which companies have actually filed for this occupation before applying.
Verify the employer's E-Verify enrollment
H-1B employers are required to participate in E-Verify. Confirm enrollment before accepting an offer. An employer not enrolled cannot legally onboard you on H-1B status, and discovering this late in the process wastes your 60-day cap-gap or grace period.
File I-129 with a detailed duties statement
AI Data Specialist is a broad title. Your employer's I-129 petition needs a specific duties statement naming the tools, models, and workflows you'll use. Vague descriptions draw RFEs questioning whether the role meets the specialty occupation standard.
Review your O*NET profile before interviews
The O*NET occupation profile for this role lists the skills, knowledge areas, and tasks USCIS references when evaluating specialty occupation status. Framing your experience in the same language strengthens both your petition and your employer's LCA documentation.
H-1B Visa AI Data Specialist: Frequently Asked Questions
Does an AI Data Specialist role qualify as an H-1B specialty occupation?
Yes. AI Data Specialist roles fall under computer and mathematical occupations, which USCIS consistently recognizes as specialty occupations requiring at least a bachelor's degree in a directly related field such as computer science, data science, statistics, or applied mathematics. The employer must document that the specific position requires that degree level in the I-129 petition.
Which employers sponsor H-1B visas for AI Data Specialist positions?
Technology companies, financial services firms, healthcare systems, and large enterprise employers with dedicated data or AI teams are the most active H-1B filers for this occupation. Migrate Mate lets you filter AI Data Specialist jobs by employers with verified DOL LCA filing history, so you can focus your search on companies that have already gone through the sponsorship process for this role.
How does the prevailing wage requirement affect AI Data Specialist H-1B petitions?
Before filing the I-129, your employer must obtain a certified LCA from DOL confirming the offered wage meets the prevailing wage for your specific job title, level, and work location. The prevailing wage is determined by DOL's OFLC Wage Search database. Wages at Level I apply to entry-level positions and Level IV to fully competent specialists with significant experience.
Can an employer file an H-1B petition for a remote AI Data Specialist role?
Yes, but the LCA must list every location where you'll physically work for more than 30 consecutive days. If your work location changes after filing, the employer may need to file an amended I-129 with an updated LCA. USCIS has scrutinized remote H-1B petitions where the worksite is ambiguous, so documenting the primary work address accurately at filing matters.
What happens to H-1B status if an AI Data Specialist is laid off?
You have a 60-day grace period from your last day of employment to find a new sponsoring employer, file a change of status, or depart the U.S. The grace period applies once per authorized validity period. If a new employer files an H-1B transfer petition before the 60 days expire, you can begin working for the new employer once USCIS receives the petition.