Staff AI Product Manager Jobs in USA with Visa Sponsorship
Staff AI Product Manager roles sit at the intersection of machine learning and product strategy, making them strong candidates for H-1B visa and O-1A sponsorship. Most require a bachelor's or master's degree in computer science, engineering, or a related technical field, with demonstrated experience leading AI or ML product development. For detailed occupation requirements, see the O*NET profile.
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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 8,566+ Staff AI Product Manager Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Staff AI Product Manager roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Staff AI Product Manager
Lead with your AI product impact, not just titles
Visa officers and hiring teams both want specificity. Quantify how your AI products performed, scaled, or improved. Approval rates for H-1B petitions in product management roles rise when the job description demonstrates clear technical and specialty occupation requirements.
Target companies with established H-1B filing histories
Large technology firms and AI-focused startups with prior H-1B approvals are far more likely to sponsor Staff-level product roles. Their legal infrastructure handles petitions efficiently, reducing delays and lowering the risk of a request for evidence on your application.
Align your degree field to the role description carefully
Staff AI PM roles typically require computer science, data science, or engineering credentials. If your degree is in business or a non-technical field, document relevant coursework, graduate certificates, or extensive ML product experience to close the specialty occupation gap.
Request cap-exempt or fiscal-year timing from your employer
If you're already in the U.S. on F-1 OPT or working at a qualifying research institution, you may qualify for cap-exempt H-1B filing. Clarify your current status with your employer early so sponsorship timelines align with your work authorization expiration date.
Build a portfolio of AI product decisions, not just features shipped
For O-1A extraordinary ability petitions, adjudicators look for evidence of original contributions. Published research, keynote invitations, peer reviews, or documented AI product frameworks you originated carry significant weight beyond standard product management credentials and outcomes.
Negotiate sponsorship terms before accepting an offer
Confirm whether the employer covers H-1B filing fees, premium processing, and legal counsel before signing. Staff-level roles typically have more negotiating leverage than junior positions, and clarifying sponsorship scope upfront prevents costly surprises during the petition process.
Frequently Asked Questions
Can a Staff AI Product Manager role qualify as a specialty occupation for H-1B purposes?
Yes, in most cases. USCIS evaluates whether the position normally requires a bachelor's degree or higher in a specific field. Staff AI PM roles that require computer science, data science, or engineering degrees, and involve technically complex work like designing ML systems or defining model evaluation frameworks, consistently satisfy the specialty occupation standard. Generic product management roles with no technical degree requirement are harder to qualify.
Does a non-technical degree disqualify me from H-1B sponsorship as an AI product manager?
Not automatically, but it creates a harder case. USCIS allows a combination of education and progressive work experience to satisfy degree equivalency, using a three-years-of-experience-per-year-of-missing-education rule. If your degree is in business or a non-STEM field, your employer's attorney will need to document that your specific AI product role requires technical expertise beyond what a generalist degree provides, which typically means attaching detailed technical job duties to the petition.
Are Staff AI Product Manager roles commonly sponsored by employers in the current market?
Yes. AI and machine learning product roles are among the most actively sponsored H-1B visa positions in the technology sector. Companies building foundation models, enterprise AI platforms, and AI-enabled SaaS products regularly file H-1B petitions for Staff PM and above. Migrate Mate surfaces sponsorship-open Staff AI PM roles specifically, so you can filter to employers who have explicitly confirmed they'll sponsor your visa rather than guessing from a job description.
What's the difference between H-1B and O-1A sponsorship for a Staff AI PM, and which is more realistic?
H-1B is the standard path and requires lottery selection unless you're cap-exempt. O-1A is lottery-free but requires evidence of extraordinary ability, such as original AI research contributions, speaking at major industry conferences, or judging peers' work. For most Staff AI PMs, H-1B is the realistic starting point. O-1A becomes viable if you have published work, significant press coverage of your product achievements, or other evidence meeting at least three of the USCIS criteria.
How much scrutiny do USCIS officers apply to AI product manager H-1B petitions compared to engineering roles?
More than engineering, less than pure business roles. USCIS has historically issued requests for evidence on product management petitions when job duties appear managerial rather than technical. Staff AI PM petitions perform best when the job description emphasizes technical responsibilities, such as defining model architectures, leading ML experimentation cycles, or collaborating directly on algorithm design, rather than roadmap management and stakeholder communication alone. Your employer's attorney should draft the petition to foreground technical duties.
What is the prevailing wage requirement for sponsored Staff AI Product Manager jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.