H-1B Visa AI Intern Jobs
AI Intern roles increasingly appear on H-1B visa petitions under SOC codes like 15-2051 (Data Scientists) and 15-1299 (Computer Occupations). Most sponsors file cap-subject petitions, so timing your offer around the April lottery window is critical. Internships tied to CPT or OPT can bridge you to a full-time H-1B sponsorship pathway.
Find H-1B Visa AI Intern JobsOverview
Showing 5 of 970+ AI Intern jobs
See all 970+ AI Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Intern roles.
Get Access To All JobsOur company
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You’ll Do
We are looking for a Senior Manager – AI Platform to lead the development and evolution of our next-generation platform powering autonomous, AI-driven agents. This role is ideal for a leader who combines data science expertise and technical depth, agentic platform thinking, and strategic execution to scale a distributed system that enables reasoning, planning, memory, and tool use at runtime.
As the Senior Manager, you will be responsible for driving product and data science strategy, overseeing a multidisciplinary team of engineers and data scientists, collaborating with AI/ML research and product teams, and ensuring that the AI Platform is performant, extensible, and production-ready.
Job Responsibilities:
- Lead the engineering and data science roadmap for the AI Platform, ensuring architectural scalability, reliability, and seamless integration with LLMs, data science pipelines.
- Partner with product, data science, research, and engineering teams to define requirements for capabilities such as predictive modeling, memory, planning, multi-agent collaboration, and tool orchestration.
- Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and data science experimentation frameworks.
- Oversee integrations with third-party tools, internal data science services, and infrastructure platforms to enable real-world agent execution and model deployment at scale.
- Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.
- Manage, mentor, and grow a high-performing team of backend engineers, data scientists, and AI platform specialists.
- Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.
- Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.
- Contribute to the long-term vision and strategy of how agentic workflows, powered by data science and machine learning, will operate at scale across the organization.
What makes you a qualified candidate
- 12+ years of experience in software/platform engineering or data science, with 3+ years in engineering management or technical leadership roles overseeing AI-driven initiatives.
- Proven experience building and scaling distributed systems or cloud platforms in production environments.
- Strong technical background in backend development, APIs, infrastructure, or platform architecture.
- Hands-on experience with AI/ML platforms, LLM integrations, and demonstrated background in data science methodologies including model development, evaluation, and deployment.
- Proven experience working with vector databases, semantic search, feature stores, and end-to-end data science pipelines in production environments.
- Strong project management skills, with a track record of delivering large cross-functional initiatives.
- Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.
- Passion for building platforms that enable intelligent, autonomous behavior at scale.
What you'll bring
- A strong track record of leading platform engineering and data science teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.
- Deep understanding of software architecture, distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.
- Experience working at the intersection of AI, data science, and engineering, ideally supporting LLM-based products, AI agents, or data science platforms that deliver measurable business value.
- A pragmatic approach to balancing technical depth with delivery speed, especially in fast-paced, R&D-heavy environments.
- Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.
- Strong cross-functional collaboration skills — able to partner effectively with product managers, researchers, infrastructure teams, and executive stakeholders.
- Curiosity and drive to push the boundaries of autonomous, data-science-powered software, and a clear vision for how data science and agentic AI systems will shape the next generation of enterprise applications.
- Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly to technical and non-technical audiences.
Why We Think You'll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.
Our company
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You’ll Do
We are looking for a Senior Manager – AI Platform to lead the development and evolution of our next-generation platform powering autonomous, AI-driven agents. This role is ideal for a leader who combines data science expertise and technical depth, agentic platform thinking, and strategic execution to scale a distributed system that enables reasoning, planning, memory, and tool use at runtime.
As the Senior Manager, you will be responsible for driving product and data science strategy, overseeing a multidisciplinary team of engineers and data scientists, collaborating with AI/ML research and product teams, and ensuring that the AI Platform is performant, extensible, and production-ready.
Job Responsibilities:
- Lead the engineering and data science roadmap for the AI Platform, ensuring architectural scalability, reliability, and seamless integration with LLMs, data science pipelines.
- Partner with product, data science, research, and engineering teams to define requirements for capabilities such as predictive modeling, memory, planning, multi-agent collaboration, and tool orchestration.
- Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and data science experimentation frameworks.
- Oversee integrations with third-party tools, internal data science services, and infrastructure platforms to enable real-world agent execution and model deployment at scale.
- Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.
- Manage, mentor, and grow a high-performing team of backend engineers, data scientists, and AI platform specialists.
- Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.
- Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.
- Contribute to the long-term vision and strategy of how agentic workflows, powered by data science and machine learning, will operate at scale across the organization.
What makes you a qualified candidate
- 12+ years of experience in software/platform engineering or data science, with 3+ years in engineering management or technical leadership roles overseeing AI-driven initiatives.
- Proven experience building and scaling distributed systems or cloud platforms in production environments.
- Strong technical background in backend development, APIs, infrastructure, or platform architecture.
- Hands-on experience with AI/ML platforms, LLM integrations, and demonstrated background in data science methodologies including model development, evaluation, and deployment.
- Proven experience working with vector databases, semantic search, feature stores, and end-to-end data science pipelines in production environments.
- Strong project management skills, with a track record of delivering large cross-functional initiatives.
- Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.
- Passion for building platforms that enable intelligent, autonomous behavior at scale.
What you'll bring
- A strong track record of leading platform engineering and data science teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.
- Deep understanding of software architecture, distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.
- Experience working at the intersection of AI, data science, and engineering, ideally supporting LLM-based products, AI agents, or data science platforms that deliver measurable business value.
- A pragmatic approach to balancing technical depth with delivery speed, especially in fast-paced, R&D-heavy environments.
- Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.
- Strong cross-functional collaboration skills — able to partner effectively with product managers, researchers, infrastructure teams, and executive stakeholders.
- Curiosity and drive to push the boundaries of autonomous, data-science-powered software, and a clear vision for how data science and agentic AI systems will shape the next generation of enterprise applications.
- Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly to technical and non-technical audiences.
Why We Think You'll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.
See all 970+ H-1B Visa AI Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI Intern Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Intern
Match your degree to the SOC code
USCIS requires a direct relationship between your degree field and the AI Intern role. A computer science or data science degree maps cleanly, but a business or economics degree may trigger an RFE unless the job description specifies technical coursework requirements.
Target employers with E-Verify enrollment
If you're on STEM OPT bridging to H-1B, your employer must be enrolled in E-Verify. Confirm enrollment before accepting an offer, not after signing, since switching employers mid-OPT restarts the verification clock.
Search LCA-verified AI sponsors on Migrate Mate
Pull up AI and machine learning roles on Migrate Mate to see which employers have filed Labor Condition Applications for this occupation. That DOL filing history tells you which companies have actually moved through the H-1B process, not just listed sponsorship as possible.
Check prevailing wage before negotiating your offer
Your employer's LCA must certify your wage at or above the DOL prevailing wage for the role's SOC code and location. Run the OFLC Wage Search before salary negotiations so you know the floor and can flag any offer that would create a filing problem.
Clarify cap-exempt status for university-affiliated roles
AI internships hosted at nonprofits affiliated with universities or at government research institutions may qualify as cap-exempt, bypassing the annual lottery. Ask directly whether the petitioning employer qualifies under INA 214(g)(5)(A) before assuming you'll need to wait for an April registration window.
Get the I-129 petition timeline in writing before you start
For intern-to-full-time conversions, confirm your employer plans to file the I-129 by April 1 for an October 1 start. A delayed filing can leave a gap between your OPT expiration and H-1B activation, even if USCIS approves the petition.
H-1B Visa AI Intern: Frequently Asked Questions
Can an internship qualify for H-1B sponsorship?
Yes, if the internship meets the specialty occupation standard, meaning the role normally requires at least a bachelor's degree in a directly related field. AI internships involving model development, data engineering, or research often qualify under computer occupations SOC codes. The employer must be willing to file an LCA with DOL and an I-129 petition with USCIS, which many larger tech and research employers do for competitive intern talent.
How do I find AI Intern employers who actually sponsor H-1B visas?
Search AI Intern roles on Migrate Mate, which surfaces employers based on verified DOL Labor Condition Application filing history. LCA filings are the clearest signal that a company has completed the H-1B sponsorship process, not just listed it as a possibility. Filtering by LCA history removes employers who say they sponsor but have no documented filings for this occupation.
Does working as an AI Intern on OPT count toward H-1B specialty occupation experience?
Yes, OPT work in an AI or data science role is treated as qualifying U.S. work experience when USCIS evaluates your H-1B petition. It strengthens the specialty occupation argument, particularly if the OPT employer is the same as the H-1B petitioner. Document your OPT role with an offer letter, pay stubs, and a detailed job description matching the technical requirements in your degree field.
What happens if I'm on STEM OPT and my AI Intern role ends before H-1B selection?
You can continue working for a different E-Verify-enrolled employer in a role related to your STEM degree without restarting your 24-month STEM OPT extension, as long as you update your SEVIS record through your DSO within five days of the job change. If no qualifying role is available, you enter a 60-day unemployment grace period. Staying within that window while pursuing new AI roles is manageable, but you'll need a new employer to file your H-1B petition in the next April registration cycle.
Do AI Intern H-1B petitions face higher RFE rates than full-time roles?
Internships can draw additional USCIS scrutiny because officers sometimes question whether a temporary role genuinely requires a degree-level specialist. The strongest defense is a detailed job description tying specific AI tasks, such as training production models or building data pipelines, to coursework in computer science or statistics. An employer with a documented track record of H-1B approvals for similar intern roles also reduces RFE risk significantly.