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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Get Access To All JobsMAIN JOB RESPONSIBILITIES / COMPETENCIES
The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.
This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.
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Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
-
Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
-
Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
-
Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
-
Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
-
Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
-
Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
-
Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
-
Establish KPIs and executive dashboards measuring AI adoption and business value.
-
Lead organizational change management and enterprise AI adoption.
-
Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
-
Evaluate emerging AI technologies and strategic technology partnerships.
-
Foster innovation, continuous improvement, and responsible AI adoption.
-
Other duties as assigned.
REQUIREMENTS
EDUCATION & TRAINING
- Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
- Advanced degree preferred.
- Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
Experience
- 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
- 3+ years leading enterprise digital AI transformation organizations.
- Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
- Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
- Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
- Experience presenting AI strategies and business outcomes to executive leadership and Boards.
- Enterprise AI governance, organizational change management, and global business transformation.
- FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
- Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
- Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
- Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
- Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
- Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
- Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
- Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
- Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
- Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
- Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
- Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.
Pay range: $200K - $300K - Final compensation/salary will depend on experience.
STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law.
LOCATION
Lake Forest, CA, US
Job Code: 2214
of Openings: 1
MAIN JOB RESPONSIBILITIES / COMPETENCIES
The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.
This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.
-
Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
-
Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
-
Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
-
Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
-
Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
-
Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
-
Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
-
Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
-
Establish KPIs and executive dashboards measuring AI adoption and business value.
-
Lead organizational change management and enterprise AI adoption.
-
Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
-
Evaluate emerging AI technologies and strategic technology partnerships.
-
Foster innovation, continuous improvement, and responsible AI adoption.
-
Other duties as assigned.
REQUIREMENTS
EDUCATION & TRAINING
- Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
- Advanced degree preferred.
- Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
Experience
- 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
- 3+ years leading enterprise digital AI transformation organizations.
- Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
- Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
- Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
- Experience presenting AI strategies and business outcomes to executive leadership and Boards.
- Enterprise AI governance, organizational change management, and global business transformation.
- FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
- Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
- Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
- Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
- Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
- Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
- Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
- Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
- Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
- Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
- Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
- Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.
Pay range: $200K - $300K - Final compensation/salary will depend on experience.
STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law.
LOCATION
Lake Forest, CA, US
Job Code: 2214
of Openings: 1
See all 1,445+ H-1B Visa Senior AI Software Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Senior AI Software Engineer Jobs.
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.