H-1B Visa AI Engineer Jobs
AI Engineer roles qualify as H-1B visa specialty occupations under the computer occupations category, typically requiring at least a bachelor's degree in computer science, machine learning, or a related field. Employers filing H-1B petitions must certify a prevailing wage through a Labor Condition Application before USCIS adjudicates your petition.
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Get Access To All JobsAbout The Team
The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time.
About The Role
We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users.
What You’ll Do
- Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows.
- Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases.
- Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation.
- Analyze failures in production and systematically improve robustness and reliability.
- Build feedback loops and data systems that get better real-task data into evaluation and research.
- Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on.
- Help define what “good” looks like for agents completing complex tasks end-to-end.
You Might Be a Good Fit If You
- Have experience building or shipping machine learning or LLM-powered products.
- Are strong in Python and comfortable with modern ML tooling.
- Have worked on model evaluation, fine-tuning, or prompt design.
- Think in terms of systems and user outcomes, not just model metrics.
- Enjoy debugging messy, real-world failures and turning them into improvements.
- Want to work in the layer that turns research and model potential into systems that actually work for users.
Bonus Points
- Experience with agent frameworks or tool-using LLM systems.
- Research experience with code generation models or developer tooling.
- Experience working with large, messy datasets or production logs.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
Compensation Range: $230K - $385K
About The Team
The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time.
About The Role
We’re looking for applied AI engineers to help bring Codex agents from impressive demos to dependable tools. This role is about improving agent performance on real software engineering tasks and closing the gap between research capability and real-world usefulness. You’ll work closely with research, infrastructure, and product to ensure agents are not just powerful, but useful, steerable, and reliable in practice. The job is not only to improve model behavior in isolation, but to turn those improvements into measurable gains in solve rate, usefulness, and economic value for users.
What You’ll Do
- Design and iterate on agent behaviors across real-world coding tasks and long-horizon workflows.
- Work closely with research to develop and run evals to measure agent performance, regressions, failure modes, and edge cases.
- Improve performance through prompting, tool-use strategies, context construction, and model-facing experimentation.
- Analyze failures in production and systematically improve robustness and reliability.
- Build feedback loops and data systems that get better real-task data into evaluation and research.
- Work with product teams to shape user-facing agent experiences and the interfaces the agent depends on.
- Help define what “good” looks like for agents completing complex tasks end-to-end.
You Might Be a Good Fit If You
- Have experience building or shipping machine learning or LLM-powered products.
- Are strong in Python and comfortable with modern ML tooling.
- Have worked on model evaluation, fine-tuning, or prompt design.
- Think in terms of systems and user outcomes, not just model metrics.
- Enjoy debugging messy, real-world failures and turning them into improvements.
- Want to work in the layer that turns research and model potential into systems that actually work for users.
Bonus Points
- Experience with agent frameworks or tool-using LLM systems.
- Research experience with code generation models or developer tooling.
- Experience working with large, messy datasets or production logs.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
Compensation Range: $230K - $385K
See all 7,818+ H-1B Visa AI Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Engineer
Verify your role meets specialty occupation criteria
AI Engineer positions must require a specific bachelor's degree to qualify for H-1B sponsorship. Check your target job description against the O*NET profile for your SOC code to confirm the degree requirement is explicit, not just preferred.
Target employers with cap-exempt filing options
Universities, nonprofit research organizations, and government research labs are cap-exempt H-1B sponsors. AI roles at these institutions let you file outside the annual lottery, giving you a year-round path that bypasses the 85,000-slot cap entirely.
Search H-1B sponsors using LCA filing history
Use Migrate Mate to filter AI Engineer roles by employers with verified LCA filing history, so you're applying only to companies that have already demonstrated willingness and infrastructure to sponsor H-1B petitions for this occupation.
Negotiate premium processing into your offer
Standard H-1B adjudication can run several months. Ask your recruiter during offer negotiation whether the employer will elect premium processing through USCIS, which guarantees a decision within 15 business days and protects your start-date timeline.
Document project work that proves specialty-level expertise
USCIS RFEs on AI Engineer petitions frequently challenge whether the role requires a theoretical and practical application of highly specialized knowledge. Compile technical documentation, model architecture write-ups, and peer-reviewed contributions before your employer files.
Confirm your wage level against OFLC Wage Search data
Your employer's LCA must certify a wage at or above the DOL prevailing wage for your SOC code and work location. Cross-check the offered salary against OFLC Wage Search before signing your offer letter to flag any compliance gap early.
H-1B Visa AI Engineer: Frequently Asked Questions
Does an AI Engineer role qualify as an H-1B specialty occupation?
AI Engineer positions qualify as H-1B specialty occupations when the job description explicitly requires at least a bachelor's degree in a specific field such as computer science, machine learning, or electrical engineering. Roles where any technical degree is acceptable, or where the requirement is listed as preferred rather than required, can trigger an RFE from USCIS. Make sure your offer letter and the employer's LCA language both reflect a specific degree requirement tied to the job duties.
Which employers sponsor H-1B visas for AI Engineers?
Technology companies, financial institutions, healthcare systems, and federal contractors all file H-1B petitions for AI Engineer roles. The most reliable way to identify active sponsors is to search employers by their LCA filing history for computer occupations. Migrate Mate filters AI Engineer jobs specifically by verified H-1B sponsorship history, so you're not applying blind to companies without a clear sponsorship track record.
How does the H-1B lottery affect AI Engineer job seekers?
USCIS opens H-1B registration each March for a lottery capped at 85,000 slots annually, with 65,000 in the regular cap and 20,000 reserved for U.S. master's degree holders. If you aren't selected, cap-exempt employers including universities and qualifying nonprofit research organizations can file outside the lottery. Some AI Engineers also pursue O-1A visas as an alternative if their work demonstrates extraordinary ability.
What documents does an employer need to file your H-1B petition as an AI Engineer?
Your employer needs a certified Labor Condition Application from DOL before filing Form I-129 with USCIS. You'll need to provide academic transcripts and a credential evaluation if your degree is from outside the U.S., your CV listing AI-specific projects and tools, and any publications or patents that support the specialty occupation argument. Employers often request a detailed job duty description matching your degree field to reduce the risk of an RFE.
Can AI Engineers on OPT work for an employer while awaiting H-1B approval?
If your H-1B petition is filed before your OPT expires and you're selected in the lottery, the cap-gap rule automatically extends your OPT employment authorization through September 30 of that fiscal year. Your employer must file before the cap-gap window opens, so confirm that your OPT end date and the H-1B filing timeline align. USCIS requires that the cap-gap extension is based on a timely filed, non-frivolous petition.