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.
Find H-1B Visa AI Engineer JobsOverview
Showing 5 of 4,814+ AI Engineer jobs
See all 4,814+ AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Engineer roles.
Get Access To All JobsWe’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.
Position Summary
The Senior Manager of AI Engineering is responsible for establishing and leading the organization's AI engineering capabilities, driving the design, development, and operationalization of enterprise-scale AI and Generative AI solutions. This leader combines deep technical expertise with strong people leadership to build high-performing engineering teams, define architectural standards, and accelerate the delivery of secure, scalable, and compliant AI platforms.
The ideal candidate is an experienced technical leader who remains hands-on with modern AI technologies, cloud-native architectures, agentic frameworks, and production AI systems. This individual will serve as the organization's technical authority for AI engineering, partnering with business and technology leaders to transform strategic opportunities into measurable business outcomes.
Primary Job Duties & Responsibilities
Organizational & Technical Leadership
- Build, lead, mentor, and develop a high-performing team of AI and software engineers while fostering a culture of innovation, accountability, and continuous learning.
- Establish the technical vision, engineering standards, and architectural roadmap for enterprise AI platforms and solutions.
- Serve as the senior technical leader for AI initiatives, providing architectural guidance, conducting design reviews, and driving key engineering decisions.
- Coach and develop engineers in system design, software engineering best practices, operational excellence, and professional growth.
- Partner with executive leadership to align AI investments, technology strategy, and delivery priorities with business objectives.
AI Strategy, Architecture & Delivery
- Define and execute the strategy for enterprise AI, Generative AI, Agentic AI, and intelligent automation initiatives.
- Lead end-to-end solution delivery across the software development lifecycle, ensuring solutions meet business, performance, scalability, reliability, security, and cost objectives.
- Evaluate emerging AI technologies, platforms, and industry trends, recommending adoption strategies and architectural standards.
- Lead production support, incident response, and operational risk management for critical AI platforms and applications.
Cloud, AI & Platform Engineering
- Provide technical leadership for cloud-native AI platforms and applications across AWS, GCP, and enterprise ecosystems.
- Guide engineering teams in the design and implementation of:
- LLM and Generative AI solutions
- Retrieval-Augmented Generation (RAG) architectures
- Agentic AI and workflow orchestration platforms
- Serverless and event-driven architectures
- APIs, microservices, and platform services
- AI observability, evaluation, and monitoring frameworks
- Establish reusable engineering patterns, frameworks, and platform accelerators that improve scalability, reliability, and delivery velocity.
Responsible AI, Security & Governance
- Ensure AI solutions align with Responsible AI principles, enterprise technology standards, security controls, and regulatory requirements.
- Partner with security, privacy, legal, compliance, and risk teams to establish governance frameworks for AI development and deployment.
- Promote best practices for model evaluation, explainability, auditability, data protection, and operational risk management.
Cross-Functional Leadership
- Partner with product, engineering, data, security, compliance, and business stakeholders to define roadmaps and prioritize initiatives.
- Communicate complex technical concepts effectively to executive leadership, technical teams, and business partners.
- Serve as a trusted advisor and thought leader on enterprise AI strategy and adoption.
Technical Expertise
The successful candidate must possess demonstrated experience designing, delivering, and leading teams responsible for the following technologies and capabilities:
AI & Cloud Engineering
- Enterprise AI platforms including AWS Bedrock, GCP Vertex AI, Azure AI, or equivalent technologies.
- Cloud-native architectures leveraging serverless, event-driven, microservices, and API-based design patterns.
Agentic AI & Intelligent Automation
- Agentic AI frameworks including Bedrock Agents, Vertex AI Agent Builder, LangGraph, LangChain, LlamaIndex, Copilot Studio, and Power Automate.
- Multi-agent systems, workflow orchestration, tool integration, reasoning, and autonomous task execution.
Retrieval-Augmented Generation (RAG)
- Enterprise RAG architectures, knowledge retrieval systems, vector search platforms, document ingestion pipelines, and enterprise data integration.
- Vector database technologies including OpenSearch, Pinecone, pgvector, FAISS, Milvus, or equivalent platforms.
AI Operations & Platform Engineering
- Model evaluation, fine-tuning, deployment, monitoring, observability, and optimization.
- AI platform scalability, governance, cost optimization, latency management, and operational excellence.
Responsible AI & Compliance
- Responsible AI governance, model documentation, risk management, validation, and auditability.
- Secure AI solution design aligned with healthcare, privacy, security, and regulatory requirements, including HIPAA.
Required Qualifications
- 7+ years of software engineering, platform engineering, machine learning, or AI engineering experience.
- 2+ years leading engineering teams or architecture initiatives, serving as a technical lead, solution architect, principal engineer, or engineering manager for enterprise-scale platforms.
- Proven experience designing, building, and operating cloud-native applications on AWS and/or GCP.
- Experience delivering production AI solutions, including Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) platforms.
- Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.
- Experience partnering within a product operating model to define technology roadmaps and deliver business outcomes.
- Exceptional communication, mentorship, and technical leadership skills with the ability to influence both technical and executive audiences.
Preferred Qualifications
- Experience operating within Agile, Scrum, and/or SAFe delivery frameworks in large enterprise environments.
- Health Care Industry experience preferred.
Education
Bachelor’s Degree in Computer Science or a related field, or equivalent experience.
Pay Range
The typical pay range for this role is:
$106,605.00 - $260,590.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full-time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 09/26/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.
Position Summary
The Senior Manager of AI Engineering is responsible for establishing and leading the organization's AI engineering capabilities, driving the design, development, and operationalization of enterprise-scale AI and Generative AI solutions. This leader combines deep technical expertise with strong people leadership to build high-performing engineering teams, define architectural standards, and accelerate the delivery of secure, scalable, and compliant AI platforms.
The ideal candidate is an experienced technical leader who remains hands-on with modern AI technologies, cloud-native architectures, agentic frameworks, and production AI systems. This individual will serve as the organization's technical authority for AI engineering, partnering with business and technology leaders to transform strategic opportunities into measurable business outcomes.
Primary Job Duties & Responsibilities
Organizational & Technical Leadership
- Build, lead, mentor, and develop a high-performing team of AI and software engineers while fostering a culture of innovation, accountability, and continuous learning.
- Establish the technical vision, engineering standards, and architectural roadmap for enterprise AI platforms and solutions.
- Serve as the senior technical leader for AI initiatives, providing architectural guidance, conducting design reviews, and driving key engineering decisions.
- Coach and develop engineers in system design, software engineering best practices, operational excellence, and professional growth.
- Partner with executive leadership to align AI investments, technology strategy, and delivery priorities with business objectives.
AI Strategy, Architecture & Delivery
- Define and execute the strategy for enterprise AI, Generative AI, Agentic AI, and intelligent automation initiatives.
- Lead end-to-end solution delivery across the software development lifecycle, ensuring solutions meet business, performance, scalability, reliability, security, and cost objectives.
- Evaluate emerging AI technologies, platforms, and industry trends, recommending adoption strategies and architectural standards.
- Lead production support, incident response, and operational risk management for critical AI platforms and applications.
Cloud, AI & Platform Engineering
- Provide technical leadership for cloud-native AI platforms and applications across AWS, GCP, and enterprise ecosystems.
- Guide engineering teams in the design and implementation of:
- LLM and Generative AI solutions
- Retrieval-Augmented Generation (RAG) architectures
- Agentic AI and workflow orchestration platforms
- Serverless and event-driven architectures
- APIs, microservices, and platform services
- AI observability, evaluation, and monitoring frameworks
- Establish reusable engineering patterns, frameworks, and platform accelerators that improve scalability, reliability, and delivery velocity.
Responsible AI, Security & Governance
- Ensure AI solutions align with Responsible AI principles, enterprise technology standards, security controls, and regulatory requirements.
- Partner with security, privacy, legal, compliance, and risk teams to establish governance frameworks for AI development and deployment.
- Promote best practices for model evaluation, explainability, auditability, data protection, and operational risk management.
Cross-Functional Leadership
- Partner with product, engineering, data, security, compliance, and business stakeholders to define roadmaps and prioritize initiatives.
- Communicate complex technical concepts effectively to executive leadership, technical teams, and business partners.
- Serve as a trusted advisor and thought leader on enterprise AI strategy and adoption.
Technical Expertise
The successful candidate must possess demonstrated experience designing, delivering, and leading teams responsible for the following technologies and capabilities:
AI & Cloud Engineering
- Enterprise AI platforms including AWS Bedrock, GCP Vertex AI, Azure AI, or equivalent technologies.
- Cloud-native architectures leveraging serverless, event-driven, microservices, and API-based design patterns.
Agentic AI & Intelligent Automation
- Agentic AI frameworks including Bedrock Agents, Vertex AI Agent Builder, LangGraph, LangChain, LlamaIndex, Copilot Studio, and Power Automate.
- Multi-agent systems, workflow orchestration, tool integration, reasoning, and autonomous task execution.
Retrieval-Augmented Generation (RAG)
- Enterprise RAG architectures, knowledge retrieval systems, vector search platforms, document ingestion pipelines, and enterprise data integration.
- Vector database technologies including OpenSearch, Pinecone, pgvector, FAISS, Milvus, or equivalent platforms.
AI Operations & Platform Engineering
- Model evaluation, fine-tuning, deployment, monitoring, observability, and optimization.
- AI platform scalability, governance, cost optimization, latency management, and operational excellence.
Responsible AI & Compliance
- Responsible AI governance, model documentation, risk management, validation, and auditability.
- Secure AI solution design aligned with healthcare, privacy, security, and regulatory requirements, including HIPAA.
Required Qualifications
- 7+ years of software engineering, platform engineering, machine learning, or AI engineering experience.
- 2+ years leading engineering teams or architecture initiatives, serving as a technical lead, solution architect, principal engineer, or engineering manager for enterprise-scale platforms.
- Proven experience designing, building, and operating cloud-native applications on AWS and/or GCP.
- Experience delivering production AI solutions, including Generative AI, Agentic AI, and Retrieval-Augmented Generation (RAG) platforms.
- Strong understanding of distributed systems, APIs, microservices, event-driven architectures, and modern software engineering practices.
- Experience partnering within a product operating model to define technology roadmaps and deliver business outcomes.
- Exceptional communication, mentorship, and technical leadership skills with the ability to influence both technical and executive audiences.
Preferred Qualifications
- Experience operating within Agile, Scrum, and/or SAFe delivery frameworks in large enterprise environments.
- Health Care Industry experience preferred.
Education
Bachelor’s Degree in Computer Science or a related field, or equivalent experience.
Pay Range
The typical pay range for this role is:
$106,605.00 - $260,590.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full-time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well-being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments.
We anticipate the application window for this opening will close on: 09/26/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
See all 4,814+ H-1B Visa AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI Engineer Jobs.
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.