H-1B Visa AI Solutions Engineer Jobs
AI Solutions Engineers design and deploy enterprise AI systems, a role USCIS consistently recognizes as a specialty occupation requiring at least a bachelor's degree in computer science, AI, or a related field. Demand for H-1B visa sponsorship in this space is high, with tech, consulting, and finance employers filing LCAs regularly for these positions.
Find H-1B Visa AI Solutions Engineer JobsOverview
Showing 5 of 1,588+ AI Solutions Engineer jobs
See all 1,588+ AI Solutions Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Solutions Engineer roles.
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.
-
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 1,588+ H-1B Visa AI Solutions Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI Solutions Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Solutions Engineer
Align your degree to the role
USCIS requires a direct connection between your degree field and the specialty occupation. A computer science, AI, or data engineering degree maps cleanly. A business degree with self-taught ML skills creates an RFE risk, document any graduate coursework or certifications that bridge the gap.
Search LCA filings by SOC code
AI Solutions Engineer roles file under SOC code 15-1252 (Software Developers) or 15-2051 (Data Scientists). Run the OFLC Wage Search filtered by those codes to identify employers already certified to sponsor H-1B workers in your target metro.
Find H-1B sponsors faster on Migrate Mate
Filter AI Solutions Engineer roles by verified H-1B filing history on Migrate Mate. You'll see which employers have active LCAs for this exact SOC code, so you're not guessing which companies will actually file a petition for you.
Clarify the employer's cap-exempt status early
Universities, nonprofits affiliated with higher education, and certain research institutions are cap-exempt, meaning they can file H-1B petitions year-round without lottery entry. If you're open to research or applied AI roles, these employers remove lottery timing risk entirely.
Request premium processing at the offer stage
Standard H-1B adjudication can run several months, which conflicts with most employer onboarding timelines. Ask your recruiter whether the company routinely pays for premium processing, USCIS upgrades to a 15-business-day decision window, before accepting an offer.
Use your 60-day grace period strategically
If your current H-1B employer does a reduction in force, you have a 60-day grace period to secure a new sponsor. A new employer can file a cap-exempt transfer petition immediately, so keep your O*NET job description documentation current and your portfolio projects publicly accessible.
H-1B Visa AI Solutions Engineer: Frequently Asked Questions
Does an AI Solutions Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, in the vast majority of cases. USCIS evaluates specialty occupation status based on whether the role normally requires a bachelor's degree or higher in a specific field. AI Solutions Engineer positions requiring expertise in machine learning, cloud architecture, or enterprise AI deployment consistently satisfy this standard. Roles where any technical degree qualifies regardless of field carry slightly higher RFE risk, so a targeted degree match strengthens your petition.
Which employers sponsor H-1B visas for AI Solutions Engineers?
Tech companies, management consulting firms, financial services institutions, and large healthcare systems are the most active H-1B sponsors for this role. Employers building internal AI platforms or selling AI-integrated products to enterprise clients file LCAs for this occupation most frequently. Browse current openings with verified H-1B filing history on Migrate Mate to see which employers are actively sponsoring right now.
How does the H-1B lottery affect my job search as an AI Solutions Engineer?
If you're subject to the annual cap, your petition enters the lottery each April for an October 1 start date. That timeline means you need an offer in hand by late March. Cap-exempt employers, universities, nonprofit research labs, and some federally funded R&D centers, can file year-round and aren't subject to the lottery, which makes them worth targeting if timing is a constraint for you.
What documentation should I prepare before applying for AI Solutions Engineer roles requiring H-1B sponsorship?
Have a degree equivalency evaluation ready if your credential is from outside the U.S., since USCIS requires confirmation it meets the U.S. bachelor's degree standard. Compile transcripts, any graduate coursework in AI or machine learning, and a portfolio of deployed AI projects. Employers' immigration counsel will use your degree field and job duties to build the specialty occupation argument, so a clear alignment between your credentials and the role description is critical.
Can an AI Solutions Engineer on H-1B switch employers mid-status?
Yes. H-1B portability allows you to start working for a new employer as soon as they file a transfer petition, without waiting for approval, as long as your prior H-1B was approved and you've maintained valid status. The new employer files a new I-129 and an LCA for the specific role and work location. You don't re-enter the lottery, and there's no gap in your work authorization if the transfer is filed before your current employment ends.