VP Of AI Jobs in USA with Visa Sponsorship
VP of AI roles attract H-1B, O-1A, and EB-1C sponsorship from tech companies, AI startups, and enterprises building out machine learning infrastructure. Most require a graduate degree in computer science or a related field, and demonstrated leadership over AI teams or products. For detailed occupation requirements, see the O*NET profile.
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INTRODUCTION
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
At The Hartford, we’re building the next generation of AI capabilities that power real business decisions—from predictive models that shape risk and pricing to AI agents that help people work smarter. To lead this effort, we are seeking a Vice President of AI Platform who brings together strong engineering discipline, practical innovation, and sound governance.
This role sits at the center of the company’s AI strategy and is responsible for shaping and operating an enterprise AI platform that supports predictive modeling, generative AI, and agent‑based systems, operating reliably across AWS and Google Cloud. Equally important, the role ensures these capabilities are safe, well governed, and trusted by the business.
The Vice President of AI Platform leads a senior organization of platform engineers, MLOps and reliability specialists, and enablement leaders, partnering closely with Data & Analytics, Security, Risk, Legal, and business leaders to enable rapid delivery aligned with enterprise standards.
This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our office locations (Hartford, CT; Charlotte, NC; Chicago, IL; Columbus, OH) will be expected to work in an office three days per week (Tuesday through Thursday). Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be authorized to work in the U.S. without company sponsorship.
KEY RESPONSIBILITIES:
- Building and Evolving the AI platform - Setting the direction for a multi‑cloud AI platform that supports a wide range of workloads—from classical predictive models to modern GenAI and multi‑agent systems. This includes establishing clear architectural standards for security, data access, identity, and deployment, while still giving teams the flexibility they need to deliver.
- Predictive Model Enablement - A core part of the platform is making predictive modeling easier to build, deploy, and operate at scale. This role will oversee standardized pipelines for features, training, validation, deployment, and monitoring. Ensuring models meet expectations around performance, explainability, fairness, and auditability – critical requirements in a regulated environment.
- AI Agents and Multi‑agent Systems – Leading the enablement of AI agents, including more advanced multi‑agent patterns where agents collaborate, review each other’s work, or operate with human oversight. Responsibilities include providing reference architectures, shared services, and guardrails so teams can build agent‑based solutions that are effective, observable, and safe.
- Agentic Analytics and Conversational BI - The platform will support conversational analytics and agent‑driven insights grounded in trusted data. This role will help establish and scale a strong semantic layer using Looker and/or Snowflake so metrics, dimensions, and predictions remain consistent, whether they’re surfaced in dashboards or through natural‑language interactions.
- Developer Experience and Enablement – This role heavily invests in developer experience, creating clear “paved paths” for teams building models and agents. This includes templates, APIs, and tooling, such as Antigravity and the Gemini CLI—that shorten the path from idea to production and reduce one‑off engineering work.
- MLOps, LLMOps, and Reliability - Running AI in production requires discipline. This leader will ensure strong practices around CI/CD, versioning, evaluation, monitoring, and rollback for both models and agents. Accountable for platform reliability, with clear SLOs, capacity planning, incident response, and cost visibility.
- Cloud Platform Operations - Supporting and standardizing SageMaker for training, experimentation, and inference on AWS. On Google Cloud, automating Vertex AI environments, pipelines, and deployments, using infrastructure‑as‑code and self‑service patterns wherever possible.
- Gemini Enterprise Enablement – The role will guide how Gemini Enterprise is adopted across the company: defining secure usage patterns, grounding strategies, access controls, and integrations that align with enterprise risk and compliance expectations.
- Governance, Risk, and Responsible AI - Working closely with Risk, Legal, Compliance, and Security to embed governance directly into the platform. This includes model and agent registries, approval workflows, lineage, audit trails, and policy enforcement, designed to protect the company without slowing innovation.
- Training and Adoption - Overseeing training and enablement for predictive modeling, AI agent development, and safe production practices. Applying a strong customer‑success lens on the platform, using feedback and adoption metrics to guide continuous improvement.
- Leadership and Influence - As a VP-level leader, this role will hire and develop strong leaders, set clear expectations, and create an environment where teams do their best work. It also partners closely with senior executives across technology and the business, communicating clearly and backing decisions with sound judgment and data.
QUALIFICATIONS:
- 15+ years of experience leading AI, ML, or platform engineering organizations at enterprise scale
- Proven ability to scale teams, platforms, and operating models in complex environments. Bachelor’s or master’s degree in computer science, engineering, or a related field (preferred)
- Deep understanding of how predictive models, LLMs, and AI agents behave in production
- Experience operating AI systems with strong discipline around reliability, performance, and lifecycle management
- Hands‑on experience designing and operating AI/ML platforms on AWS and Google Cloud
- Strong working knowledge of training, experimentation, inference, and pipeline orchestration in cloud environments
- Expertise across feature pipelines, evaluation metrics, CI/CD, monitoring, and rollback strategies
- Ability to make and explain tradeoffs between reliability, scalability, cost, and speed
- Demonstrated experience partnering with Risk, Legal, Compliance, and Security teams
- Strong understanding of governance controls required in regulated enterprise environments
- Ability to communicate complex technical topics clearly to senior executives and business leaders
- Trusted partner to technology and business stakeholders, with sound judgment backed by data
- Experience leading large, distributed teams through clear expectations and strong talent development
- Proven track record of translating strategy into measurable outcomes, with accountability for execution and results.
COMPENSATION
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition. The annualized base pay range for this role is:
$222,480 - $333,720
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

INTRODUCTION
We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.
At The Hartford, we’re building the next generation of AI capabilities that power real business decisions—from predictive models that shape risk and pricing to AI agents that help people work smarter. To lead this effort, we are seeking a Vice President of AI Platform who brings together strong engineering discipline, practical innovation, and sound governance.
This role sits at the center of the company’s AI strategy and is responsible for shaping and operating an enterprise AI platform that supports predictive modeling, generative AI, and agent‑based systems, operating reliably across AWS and Google Cloud. Equally important, the role ensures these capabilities are safe, well governed, and trusted by the business.
The Vice President of AI Platform leads a senior organization of platform engineers, MLOps and reliability specialists, and enablement leaders, partnering closely with Data & Analytics, Security, Risk, Legal, and business leaders to enable rapid delivery aligned with enterprise standards.
This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our office locations (Hartford, CT; Charlotte, NC; Chicago, IL; Columbus, OH) will be expected to work in an office three days per week (Tuesday through Thursday). Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be authorized to work in the U.S. without company sponsorship.
KEY RESPONSIBILITIES:
- Building and Evolving the AI platform - Setting the direction for a multi‑cloud AI platform that supports a wide range of workloads—from classical predictive models to modern GenAI and multi‑agent systems. This includes establishing clear architectural standards for security, data access, identity, and deployment, while still giving teams the flexibility they need to deliver.
- Predictive Model Enablement - A core part of the platform is making predictive modeling easier to build, deploy, and operate at scale. This role will oversee standardized pipelines for features, training, validation, deployment, and monitoring. Ensuring models meet expectations around performance, explainability, fairness, and auditability – critical requirements in a regulated environment.
- AI Agents and Multi‑agent Systems – Leading the enablement of AI agents, including more advanced multi‑agent patterns where agents collaborate, review each other’s work, or operate with human oversight. Responsibilities include providing reference architectures, shared services, and guardrails so teams can build agent‑based solutions that are effective, observable, and safe.
- Agentic Analytics and Conversational BI - The platform will support conversational analytics and agent‑driven insights grounded in trusted data. This role will help establish and scale a strong semantic layer using Looker and/or Snowflake so metrics, dimensions, and predictions remain consistent, whether they’re surfaced in dashboards or through natural‑language interactions.
- Developer Experience and Enablement – This role heavily invests in developer experience, creating clear “paved paths” for teams building models and agents. This includes templates, APIs, and tooling, such as Antigravity and the Gemini CLI—that shorten the path from idea to production and reduce one‑off engineering work.
- MLOps, LLMOps, and Reliability - Running AI in production requires discipline. This leader will ensure strong practices around CI/CD, versioning, evaluation, monitoring, and rollback for both models and agents. Accountable for platform reliability, with clear SLOs, capacity planning, incident response, and cost visibility.
- Cloud Platform Operations - Supporting and standardizing SageMaker for training, experimentation, and inference on AWS. On Google Cloud, automating Vertex AI environments, pipelines, and deployments, using infrastructure‑as‑code and self‑service patterns wherever possible.
- Gemini Enterprise Enablement – The role will guide how Gemini Enterprise is adopted across the company: defining secure usage patterns, grounding strategies, access controls, and integrations that align with enterprise risk and compliance expectations.
- Governance, Risk, and Responsible AI - Working closely with Risk, Legal, Compliance, and Security to embed governance directly into the platform. This includes model and agent registries, approval workflows, lineage, audit trails, and policy enforcement, designed to protect the company without slowing innovation.
- Training and Adoption - Overseeing training and enablement for predictive modeling, AI agent development, and safe production practices. Applying a strong customer‑success lens on the platform, using feedback and adoption metrics to guide continuous improvement.
- Leadership and Influence - As a VP-level leader, this role will hire and develop strong leaders, set clear expectations, and create an environment where teams do their best work. It also partners closely with senior executives across technology and the business, communicating clearly and backing decisions with sound judgment and data.
QUALIFICATIONS:
- 15+ years of experience leading AI, ML, or platform engineering organizations at enterprise scale
- Proven ability to scale teams, platforms, and operating models in complex environments. Bachelor’s or master’s degree in computer science, engineering, or a related field (preferred)
- Deep understanding of how predictive models, LLMs, and AI agents behave in production
- Experience operating AI systems with strong discipline around reliability, performance, and lifecycle management
- Hands‑on experience designing and operating AI/ML platforms on AWS and Google Cloud
- Strong working knowledge of training, experimentation, inference, and pipeline orchestration in cloud environments
- Expertise across feature pipelines, evaluation metrics, CI/CD, monitoring, and rollback strategies
- Ability to make and explain tradeoffs between reliability, scalability, cost, and speed
- Demonstrated experience partnering with Risk, Legal, Compliance, and Security teams
- Strong understanding of governance controls required in regulated enterprise environments
- Ability to communicate complex technical topics clearly to senior executives and business leaders
- Trusted partner to technology and business stakeholders, with sound judgment backed by data
- Experience leading large, distributed teams through clear expectations and strong talent development
- Proven track record of translating strategy into measurable outcomes, with accountability for execution and results.
COMPENSATION
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition. The annualized base pay range for this role is:
$222,480 - $333,720
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
How to Get Visa Sponsorship in VP Of AI
Lead with measurable AI outcomes
USCIS and hiring teams both want evidence of impact. Quantify model performance gains, revenue driven by AI products, or team scale. Concrete metrics strengthen your H-1B petition and distinguish you from other senior candidates.
Target companies with AI as a core product
Companies where AI is central to the business, not just a supporting function, are far more likely to sponsor. They have established immigration counsel, faster internal approval processes, and stronger incentive to secure visa status for critical leadership hires.
Understand the O-1A path
VP-level AI candidates with publications, speaking engagements, open-source contributions, or industry awards may qualify for O-1A extraordinary ability. It has no lottery and no annual cap, making it a strong alternative if H-1B selection is uncertain.
A graduate degree significantly helps
Most VP of AI roles require a master's or Ph.D. in computer science, machine learning, or a related field for specialty occupation classification. A strong advanced degree narrows the USCIS definition of the role and reduces the risk of an RFE.
Frame your experience around team leadership, not just technical depth
VP roles require demonstrating managerial authority over AI teams, not just hands-on model building. Petitions that clearly separate executive scope from individual contributor work are more persuasive to USCIS reviewers assessing specialty occupation status.
Ask about EB-1C intent early
Some companies hiring for VP of AI roles are open to sponsoring EB-1C green cards, which are reserved for multinational executives and managers. If you have prior leadership tenure at a related entity abroad, raise this pathway with the employer before accepting an offer.
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Get Access To All JobsFrequently Asked Questions
Does a VP of AI role qualify as a specialty occupation for H-1B purposes?
Generally yes, but the petition needs to show the role requires a specific bachelor's degree or higher in a relevant field, not just any degree. USCIS scrutinizes senior leadership titles carefully, so the job description must emphasize the technical depth required, not just managerial responsibility. Roles at companies where AI is the core product tend to have stronger petitions.
What visa types do employers typically sponsor for VP of AI positions?
H-1B is the most common starting point, but O-1A is increasingly used for candidates with a strong public profile in AI, such as publications, conference presentations, or open-source work with demonstrated community adoption. EB-1C immigrant visa sponsorship is also possible for candidates who previously led AI teams at a related entity outside the U.S.
Is a Ph.D. required to get H-1B sponsorship as a VP of AI?
A Ph.D. is not strictly required, but it strengthens the specialty occupation argument considerably. A master's degree in computer science, machine learning, or a related technical field is the more common baseline. Candidates without a graduate degree typically need extensive, well-documented experience in a directly related technical discipline to support the petition.
How can I find VP of AI jobs that offer visa sponsorship?
Most senior AI leadership roles that include sponsorship are not widely advertised as such, since companies vary in how they disclose immigration support in job postings. Migrate Mate filters specifically for roles that offer visa sponsorship, so you can focus on VP of AI openings at companies that have already committed to supporting international candidates.
Can a VP of AI on H-1B status change employers without losing status?
Yes. H-1B portability allows you to start working for a new employer as soon as the new H-1B petition is filed, provided your current status is valid and there was no gap in authorized employment. The new employer must file a new cap-exempt H-1B petition before your last day, and you should not let your status lapse between roles.
What is the prevailing wage requirement for sponsored VP Of AI 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.
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