H-1B Visa Generative AI Engineer Jobs
Generative AI Engineer roles sit squarely within H-1B visa specialty occupation requirements, typically classified under SOC codes for software developers or computer and information research scientists. Employers filing LCAs for these positions must meet DOL prevailing wage standards, and the annual H-1B cap means timing your job search around the April lottery window matters.
Find H-1B Visa Generative AI Engineer JobsOverview
Showing 5 of 56+ Generative AI Engineer jobs
See all 56+ Generative AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Generative AI Engineer roles.
Get Access To All JobsTitle: Senior Developer
Location: Columbia, SC - Partially onsite - 3 days per week (Tue, Wed, Thurs) and as needed.
Duration: 11 months
Standard work hours: 8:00 AM – 5:00 PM
Credit check will be required
Job Description:
This is a new role to establish a core competency in agentic AI systems. This engineer will be pivotal in designing and deploying advanced AI agents and will build the foundational frameworks for future AI use cases across the organization.
Day to Day:
- A typical day will involve a mix of hands-on coding, architectural design, and research. The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
- This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
- They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
Team:
The team is an innovative, collaborative, and empowering environment. We are building the next generation of AI solutions for the enterprise in a fast-paced, project-oriented setting. This is a multi-platformed environment that values creativity, continuous learning, and a customer-focused mindset. The new engineer will play a crucial role in shaping our AI strategy and building foundational tools and accelerators that will drive innovation across the company.
NOT Looking for:
We are not looking for candidates whose primary experience is in data analytics or traditional machine learning (e.g., regression, classification) without significant exposure to Generative AI.
Minimum Required Education:
Bachelor's degree in Computer Science, Information Technology or other job related degree or 4 years relevant experience or Associates degree + 2 years relevant experience
Minimum Required Work Experience:
8 years of application development, systems testing or other job related experience. (6 yrs for Dev IV)
Required Technologies:
- 3–6 years of hands-on experience in Artificial Intelligence, Machine Learning, or related fields.
- Python & AI/ML Libraries: Deep hands-on experience in Python for AI/ML development.
- Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
- Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
- Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
Tech Stack:
- Python
- JavaScript/TypeScript
- AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
- AI Models (e.g. Claude, OpenAI, etc.)
- AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
- Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
- Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
- API Design
Nice to Have:
- Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
- Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
- Experience developing autonomous agents using cloud-based AI services.
- Experience with prompt engineering techniques and model fine-tuning.
- Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
- Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
Title: Senior Developer
Location: Columbia, SC - Partially onsite - 3 days per week (Tue, Wed, Thurs) and as needed.
Duration: 11 months
Standard work hours: 8:00 AM – 5:00 PM
Credit check will be required
Job Description:
This is a new role to establish a core competency in agentic AI systems. This engineer will be pivotal in designing and deploying advanced AI agents and will build the foundational frameworks for future AI use cases across the organization.
Day to Day:
- A typical day will involve a mix of hands-on coding, architectural design, and research. The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
- This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
- They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
Team:
The team is an innovative, collaborative, and empowering environment. We are building the next generation of AI solutions for the enterprise in a fast-paced, project-oriented setting. This is a multi-platformed environment that values creativity, continuous learning, and a customer-focused mindset. The new engineer will play a crucial role in shaping our AI strategy and building foundational tools and accelerators that will drive innovation across the company.
NOT Looking for:
We are not looking for candidates whose primary experience is in data analytics or traditional machine learning (e.g., regression, classification) without significant exposure to Generative AI.
Minimum Required Education:
Bachelor's degree in Computer Science, Information Technology or other job related degree or 4 years relevant experience or Associates degree + 2 years relevant experience
Minimum Required Work Experience:
8 years of application development, systems testing or other job related experience. (6 yrs for Dev IV)
Required Technologies:
- 3–6 years of hands-on experience in Artificial Intelligence, Machine Learning, or related fields.
- Python & AI/ML Libraries: Deep hands-on experience in Python for AI/ML development.
- Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
- Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
- Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
Tech Stack:
- Python
- JavaScript/TypeScript
- AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
- AI Models (e.g. Claude, OpenAI, etc.)
- AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
- Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
- Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
- API Design
Nice to Have:
- Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
- Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
- Experience developing autonomous agents using cloud-based AI services.
- Experience with prompt engineering techniques and model fine-tuning.
- Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
- Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
See all 56+ H-1B Visa Generative AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Generative AI Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Generative AI Engineer
Verify your role qualifies as specialty occupation
Generative AI Engineer positions must require a bachelor's degree or higher in a directly related field. Check the O*NET profile for your SOC code to confirm the degree requirement, since USCIS scrutinizes AI roles where job duties could theoretically be filled without a specific degree.
Target employers with active LCA filing history
Use Migrate Mate to filter employers by verified DOL Labor Condition Application filings for AI and machine learning roles, so you're applying to companies that have already committed to the H-1B process rather than ones exploring it for the first time.
Document proprietary model work for your petition
USCIS officers evaluating AI engineer petitions look for evidence the role requires specialized theoretical knowledge. Keep records of your work with foundation models, fine-tuning pipelines, and architecture decisions. These specifics strengthen the specialty occupation argument in your I-129 filing.
Register before the March cap-subject lottery deadline
H-1B registration opens each March for the following fiscal year's cap. If you're on OPT, confirm your authorization end date against the October 1 start date. A cap-gap protects your status if your OPT expires between April selection and October 1, but only if your employer files on time.
Clarify remote and hybrid work in your LCA before filing
DOL requires a separate LCA or amended filing if your worksite changes. For generative AI roles with flexible remote arrangements, confirm with your employer whether the LCA lists your home address or a corporate office, since a mismatch is one of the most common audit triggers.
Flag cap-exempt employers during your search
Universities, nonprofit research organizations, and government entities are exempt from the H-1B annual cap. Generative AI research roles at these institutions can be filed any time of year, bypassing the lottery entirely. These opportunities are worth pursuing in parallel with cap-subject employer applications.
H-1B Visa Generative AI Engineer: Frequently Asked Questions
Does a Generative AI Engineer role qualify as an H-1B specialty occupation?
Yes, in most cases. USCIS defines specialty occupation as a role requiring at least a bachelor's degree in a directly related field. Generative AI Engineer positions typically require a degree in computer science, machine learning, or a closely related discipline. The O*NET classification for your specific SOC code is the starting point for confirming this. Roles where any degree field is acceptable are harder to defend under specialty occupation criteria.
Which employers are most likely to sponsor H-1B visas for Generative AI Engineers?
Employers with established H-1B programs and prior LCA filings for AI and software roles are the most reliable sponsors. You can find these employers on Migrate Mate, which surfaces verified DOL LCA filing history filtered by occupation. Large tech companies, AI research labs, and cloud platform providers file the most petitions in this space, but mid-size startups building generative AI products increasingly sponsor as well.
How does the prevailing wage requirement apply to Generative AI Engineer roles?
Your employer must pay at least the DOL prevailing wage for your SOC code in the worksite location before USCIS will approve the petition. Generative AI roles often map to Level III or Level IV wage tiers given the seniority and specialization involved. You can look up the applicable wage using the OFLC Wage Search tool. The wage listed on your LCA must match or exceed that figure.
Can a Generative AI Engineer change employers on an H-1B?
Yes. H-1B portability under AC21 lets you start working for a new employer as soon as they file a new I-129 petition, without waiting for approval, as long as your previous petition was approved and you've been in H-1B status for at least 180 days. Your new employer files a fresh LCA with the DOL for the new worksite and role before submitting the I-129 to USCIS.
Does remote work affect an H-1B petition for a Generative AI Engineer?
It can. The DOL requires the LCA to list the actual worksite where you perform the work. If you're fully remote, the LCA must cover your home address location. Working from an unlisted location, even temporarily, can trigger compliance issues during a DOL audit. Discuss the worksite structure with your employer before the LCA is certified to avoid an amended filing later.