H-1B Visa AI Specialist Jobs
AI Specialist roles qualify as H-1B visa specialty occupations under the computer occupations category, requiring at least a bachelor's degree in computer science, artificial intelligence, or a directly related field. Employers filing H-1B petitions for these roles must certify a prevailing wage through a DOL Labor Condition Application before USCIS can approve your petition.
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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 1,172+ H-1B Visa AI Specialist Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Specialist
Align your degree field to the role
USCIS scrutinizes whether your degree directly relates to AI Specialist duties. A degree in computer science or machine learning aligns cleanly. A business or general STEM degree needs supporting coursework transcripts or a credential evaluation to survive an RFE.
Check the prevailing wage before negotiating
Your employer's LCA must certify a wage at or above the DOL prevailing wage for your specific SOC code and work location. Use the OFLC Wage Search to verify the Level I through Level IV wage tiers before you accept an offer.
Target employers with cap-exempt affiliations
AI research roles at universities, nonprofit research institutions, and government-affiliated labs are cap-exempt, meaning your employer can file your H-1B petition outside the annual lottery window at any time of year.
Search LCA filing history on Migrate Mate
Before applying, verify that a company has actually filed H-1B Labor Condition Applications for AI roles. Migrate Mate surfaces DOL LCA filing history by employer and occupation code so you can confirm sponsorship history before reaching the offer stage.
Document your AI specialization precisely
USCIS O*NET classifies AI Specialist duties at Job Zone 4 and above. Your resume and the employer's support letter must map your specific tasks, such as training large language models or designing neural network architectures, to those defined specialty occupation duties.
File premium processing if your start date is fixed
If your employment start date is tied to a project deadline or OPT expiration, ask your employer to file premium processing with Form I-907. USCIS guarantees a decision within 15 business days, reducing the risk of a gap in work authorization.
H-1B Visa AI Specialist: Frequently Asked Questions
Does an AI Specialist role qualify as an H-1B specialty occupation?
Yes. USCIS classifies AI Specialist positions under computer occupations, which consistently meet the specialty occupation standard because the role normally requires at least a bachelor's degree in computer science, data science, artificial intelligence, or a closely related field. If your job description includes tasks like model development, algorithm design, or ML pipeline engineering, the specialty occupation requirement is typically straightforward to satisfy.
Which employers sponsor H-1B visas for AI Specialist roles?
Technology companies, financial institutions running quantitative or risk modeling teams, healthcare systems building clinical AI tools, and defense contractors with AI research divisions are among the most active H-1B sponsors for these roles. Migrate Mate filters employers by DOL Labor Condition Application filing history, so you can identify companies that have sponsored AI Specialist positions rather than relying on job postings alone.
What happens to my H-1B status if I change AI Specialist roles mid-petition?
If you change employers after your H-1B petition is filed but before October 1, your new employer must file a fresh cap-subject petition in the next lottery cycle unless you already have an approved H-1B from a prior year. If you're transferring to a new employer after your H-1B is already active, your new employer files an H-1B transfer petition and you can start work as soon as USCIS receives it, under the portability provisions of AC21.
Can a startup sponsor my H-1B as an AI Specialist?
Yes, but startups face additional scrutiny. USCIS may issue an RFE questioning whether the company has enough complexity to require a specialty occupation hire, or whether an employer-employee relationship exists if you have equity or a board seat. Your employer's support letter should clearly define your supervised role, your reporting structure, and the specific AI projects requiring your degree-level expertise.
How does the H-1B lottery affect AI Specialist job searches?
The annual H-1B cap covers most private-sector AI Specialist roles, with registrations submitted in March and selections made before April 1 for an October 1 start date. If you're not selected, cap-exempt options include roles at qualifying nonprofit research organizations, universities, or government research facilities. F-1 OPT or STEM OPT authorization can bridge the gap while you wait for the next lottery cycle.