H-1B Visa Senior AI Software Engineer Jobs
Senior AI Software Engineer roles sit squarely within H-1B visa specialty occupation criteria, requiring at minimum a bachelor's degree in computer science, machine learning, or a related field. Employers filing H-1B petitions for this role must certify a prevailing wage through the DOL, and cap-subject filings enter the annual lottery each March.
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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 1,197+ H-1B Visa Senior AI Software Engineer Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Senior AI Software Engineer
Map your degree to specialty occupation criteria
USCIS evaluates whether your degree field directly relates to AI engineering work. A computer science or machine learning degree is straightforward, but adjacent fields like applied mathematics or electrical engineering need a clear narrative tying coursework to the role's technical requirements.
Use OFLC Wage Search before negotiating salary
Pull the prevailing wage for your SOC code and target metro area before your offer stage. Employers must pay at least the DOL-certified wage level, so knowing Level III or IV thresholds for AI roles gives you a grounded starting point and signals you understand the filing process.
Filter employers by active H-1B LCA filing history
On Migrate Mate, you can search Senior AI Software Engineer roles filtered to employers with verified H-1B Labor Condition Application filing history, so you're not spending time on companies that have never sponsored this visa category.
Target cap-exempt employers for faster timelines
Universities, nonprofit research institutions, and certain government-affiliated labs are exempt from the annual H-1B cap and lottery. AI research roles at these organizations can be filed at any time of year, bypassing the March registration window and the 60-day waiting period entirely.
Confirm your employer is E-Verify enrolled before accepting
H-1B petitions can only be filed by employers registered with E-Verify. Smaller AI startups sometimes aren't enrolled, which delays or blocks your petition. Ask HR directly before signing, since enrollment takes time and can't be backdated to your start date.
Prepare your O*NET profile match for RFE risk
USCIS regularly issues Requests for Evidence on AI engineering roles when the degree-to-job connection isn't explicit. Pull the O*NET occupation profile for your job code and document how your specific duties align with the listed tasks and required knowledge areas before your employer submits.
H-1B Visa Senior AI Software Engineer: Frequently Asked Questions
Does a Senior AI Software Engineer role qualify as an H-1B specialty occupation?
Yes. USCIS treats software engineering positions requiring a bachelor's degree or higher in computer science, machine learning, or a directly related field as specialty occupations. For senior-level AI roles, the combination of advanced technical requirements and degree specificity typically satisfies all four specialty occupation criteria. The employer's job description must clearly state the degree requirement, not just prefer it.
Which employers sponsor H-1B visas for AI engineering roles?
Large technology companies, AI-focused startups with institutional backing, cloud platform providers, financial services firms building quantitative systems, and university research labs all regularly sponsor H-1B visas for senior AI engineering positions. Migrate Mate lists employers with verified H-1B LCA filing history specifically for this role, so you can prioritize outreach to companies that have already gone through the process.
How does the H-1B cap lottery affect senior AI engineers specifically?
Cap-subject H-1B petitions are limited to 85,000 new visas per fiscal year, with registration opening each March. Selection is random, not merit-based, so a strong AI background doesn't improve your odds in the general pool. If you're currently on OPT or STEM OPT, timing your job search to align with the March registration window is critical for maintaining continuous work authorization.
Can an AI engineering role justify H-1B approval without a computer science degree?
Sometimes. USCIS accepts equivalent experience under a three-for-one rule, where three years of progressively specialized AI engineering experience substitutes for one year of a bachelor's degree. A master's or Ph.D. in a related field like statistics or electrical engineering can also qualify, provided the employer documents how that degree directly prepares someone for the specific AI responsibilities in the role description.
What happens to my H-1B status if I'm laid off from an AI engineering job?
You have a 60-day grace period after involuntary termination to find a new H-1B employer, change to another nonimmigrant status, or depart the country. Your new employer must file a transfer petition before the grace period ends. Maintaining documentation of your layoff date and any active job search is important, since USCIS may scrutinize the timeline during a transfer petition review.