H-1B Visa AI Platform Engineer Jobs
AI Platform Engineer roles sit squarely within H-1B visa specialty occupation territory, requiring at least a bachelor's degree in computer science, machine learning, or a related field. Employers filing LCAs for this role typically classify it under SOC codes tied to software development or computer and information research, which affects your prevailing wage tier and petition strength.
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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 1,417+ H-1B Visa AI Platform Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI Platform Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Platform Engineer
Align your SOC code before negotiating
AI Platform Engineer roles get filed under different SOC codes depending on the employer, most often 15-1252 or 15-1299. The code drives your prevailing wage tier, so confirm which one your employer plans to use before the LCA is submitted.
Document your ML infrastructure work specifically
USCIS increasingly issues RFEs for platform engineering roles, questioning whether the position requires a specialty degree. Gather project artifacts, architecture diagrams, and performance benchmarks that tie your work directly to applied machine learning systems.
Search LCA filings to find proven sponsors
Use Migrate Mate to filter employers by verified H-1B LCA filing history for AI and platform engineering roles, so you're targeting companies that have already cleared the DOL certification process for positions like yours.
Check E-Verify enrollment before accepting an offer
If you're on STEM OPT and transitioning to H-1B, your current employer must be E-Verify enrolled. Confirm enrollment status with HR before your OPT end date, because a gap in authorization can't be retroactively fixed.
Use OFLC Wage Search to anchor your salary ask
Pull the prevailing wage for your target SOC code and work location using OFLC Wage Search before your offer conversation. Employers must pay at least the prevailing wage on the LCA, so knowing Level II versus Level III thresholds gives you a factual floor.
Time your cap-gap window against project timelines
If you're bridging OPT to H-1B under cap-gap, your authorization extends through September 30 but work authorization ends if USCIS denies the petition. Avoid accepting roles with critical delivery milestones that fall after that date without a contingency plan.
H-1B Visa AI Platform Engineer: Frequently Asked Questions
Does an AI Platform Engineer role qualify as a specialty occupation for H-1B purposes?
Yes, provided the position genuinely requires at least a bachelor's degree in a directly related field such as computer science, software engineering, or machine learning. USCIS scrutinizes platform engineering titles more than pure software roles, so the job description must clearly tie day-to-day responsibilities to a specific theoretical body of knowledge, not just general technical skill.
Which SOC code do employers typically use when filing H-1B petitions for AI Platform Engineers?
Most employers file under SOC 15-1252 (Software Developers) or 15-1299 (Computer Occupations, All Other), depending on how the role is structured. The SOC code determines the prevailing wage level your employer must certify on the LCA. You can verify which codes appear most often for this title by reviewing DOL disclosure data or searching employer LCA filings on Migrate Mate.
What makes H-1B RFEs more likely for AI Platform Engineer positions?
USCIS issues RFEs when the specialty occupation connection isn't obvious from the job description alone. Broad titles like 'platform engineer' or responsibilities that mix DevOps, infrastructure, and ML without anchoring them to a specific degree field raise adjudicator questions. Including architecture documentation, ML system design artifacts, and degree-specific role requirements in the initial petition significantly reduces RFE risk.
How do I find employers actively sponsoring H-1B visas for AI Platform Engineer roles?
Search Migrate Mate to browse AI Platform Engineer jobs filtered by employers with verified H-1B LCA filing history. This surfaces companies that have already completed DOL labor condition certification for similar roles, meaning they're familiar with the sponsorship process and less likely to withdraw an offer when they see the filing requirements.
Can my employer use premium processing for an AI Platform Engineer H-1B petition?
Yes. Premium processing is available for H-1B petitions and guarantees a USCIS decision within 15 business days. It's particularly useful for AI Platform Engineer roles where RFEs are more common, because a faster initial decision leaves more time to respond without disrupting your start date. Employers typically pay the premium processing fee, but confirm this during your offer negotiation.