H-1B Visa Software Engineer AI Jobs
Software Engineer AI roles sit squarely within H-1B visa specialty occupation requirements, making them strong candidates for sponsorship. Employers filing Labor Condition Applications for these positions must meet DOL prevailing wage standards, and many actively sponsor H-1B transfers for candidates already in status.
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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 1,198+ H-1B Visa Software Engineer AI Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Software Engineer AI Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship in Software Engineer AI
Align your resume to SOC codes
AI engineering roles map to specific Standard Occupational Classification codes that employers use when filing LCAs with DOL. Check the O*NET profile for your target title and mirror that language in your resume to strengthen your specialty occupation case.
Target employers with LCA filing history
Use Migrate Mate to filter Software Engineer AI roles by verified DOL Labor Condition Application data, so you're applying to employers who have already navigated H-1B sponsorship for this occupation rather than asking them to start from scratch.
Verify the employer's E-Verify enrollment early
STEM OPT employers must be E-Verify participants, and many H-1B sponsors are as well. Confirm enrollment before accepting an offer, not after, since an unenrolled employer can't legally proceed with your authorization without registering first.
Document your AI specialization with project artifacts
USCIS officers scrutinize whether an AI engineering role genuinely requires a specialty degree. Prepare a portfolio showing model architectures, published work, or proprietary system contributions that demonstrate the theoretical and applied depth the petition needs to support.
Negotiate LCA wage level placement before signing
DOL assigns prevailing wage levels one through four based on experience and complexity. Accepting a Level 1 placement when your role involves independent research or system design can underpay you and signal to USCIS that the position lacks the seniority its title implies.
H-1B Visa Software Engineer AI: Frequently Asked Questions
Do Software Engineer AI roles qualify as H-1B specialty occupations?
Yes. Software Engineer AI positions require at least a bachelor's degree in computer science, machine learning, or a directly related field, which satisfies the specialty occupation definition under USCIS guidelines. Roles involving model development, neural architecture design, or applied research carry particularly strong qualification arguments because the theoretical depth of the degree is directly tied to the daily work.
How do I find employers actively sponsoring H-1B visas for AI engineering roles?
Migrate Mate filters Software Engineer AI listings by verified DOL Labor Condition Application filing history, so every employer you see has a documented record of sponsoring H-1B workers in comparable roles. This saves you from applying to companies that list AI roles but have never navigated the sponsorship process for this occupation category.
Can I transfer my H-1B to a new AI engineering employer mid-status?
Yes. Under H-1B portability rules, you can begin working for a new employer as soon as they file a non-frivolous I-129 transfer petition, without waiting for approval, provided you've been in valid H-1B status and haven't accrued unlawful presence. The new employer files a fresh LCA with DOL and an I-129 with USCIS listing the AI engineering role details.
What prevailing wage level should a Software Engineer AI role fall under?
Most mid-level and senior AI engineering positions warrant a Level 3 or Level 4 prevailing wage under DOL's OFLC Wage Search, reflecting the independent judgment and specialized expertise the work requires. Accepting a Level 1 or Level 2 placement for a role involving original model development or research can create inconsistencies that USCIS may flag during adjudication.
Does working on proprietary AI systems strengthen or complicate an H-1B petition?
It strengthens it. Proprietary system work demonstrates that the role requires specific, non-generic knowledge tied to a degree-level theoretical foundation, which directly supports the specialty occupation argument. Be prepared to provide a detailed job duties letter from your employer describing the systems you work on, the degree requirements they impose, and why the work can't be performed without that educational background.