Green Card AI Data Specialist Jobs
AI Data Specialist roles qualify for EB-2 and EB-3 green card sponsorship through the PERM labor certification process, which requires employers to document that no qualified U.S. worker is available. Roles involving machine learning pipelines, data labeling systems, and AI model training commonly meet the specialty occupation and degree requirements that support a permanent sponsorship petition.
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Get Access To All JobsWe are seeking a strategic and hands-on Director, AI Engineering to lead the design, development, and scaling of Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on building AI applications and reusable AI platform capabilities powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP), multi-agent systems, Agentic AI platforms, and modern AI/ML infrastructure across the enterprise for both internal and customer-facing use cases.
The ideal candidate combines deep expertise in a modern AI/ML stack with strong AI software engineering fundamentals, strong people leadership, and the ability to partner effectively across technology, data, product, operations, and business teams.
You will help define the AI engineering strategy and roadmap, lead a high-performing AI Engineering team, build and manage scalable AI products, establish standards for scalable and secure AI delivery, and help translate AI investments into measurable business outcomes.
Key Responsibilities
- Help to define and lead the execution of AI engineering strategy, target architecture, and roadmap for Generative and Agentic AI across the enterprise.
- Manage and motivate a high-performing team of AI engineers including coaching, mentoring, and scaling as required.
- Design, build, and oversee deployment of scalable LLM-powered applications and AI-native products for customer support, business operations, and internal productivity.
- Lead the development of AI agents, agentic platforms, and autonomous workflows capable of reasoning, planning, and executing multi-step tasks.
- Implement RAG architectures and pipelines to leverage proprietary data, internal knowledge bases, enterprise systems, and structured/unstructured content.
- Stand-up and evolve MCP servers, tool integrations, and multi-connectivity AI platforms to support secure orchestration across internal and external systems.
- Establish and oversee standards for prompt design, model evaluation, guardrails, observability, testing, and production readiness to ensure accuracy, resiliency, security, and regulatory compliance.
- Lead the design of MLOps and LLMOps pipelines for model lifecycle management, monitoring, continuous evaluation, and improvement.
- Leverage CI/CD and Agile methodologies for AI product development.
- Partner with architecture, security, legal, compliance, and data teams to ensure AI solutions meet requirements for privacy, governance, auditability, and responsible AI.
- Drive build vs. buy decisions, vendor selection, and collaboration with external partners, consultants, and internal teams to deliver scalable, high-quality AI solutions.
- Work closely with business leaders to identify and prioritize high-value use cases across the insurance business, process optimization, software development, and employee productivity.
- Define and track success metrics for adoption, quality, reliability, business impact, cost efficiency, and delivery velocity.
- Stay current with emerging advancements in AI/ML, Generative AI, agentic frameworks, model architectures, and enterprise AI engineering practices.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related field. Graduate degrees are preferred, but not necessary.
- 10+ years of experience in software engineering, platform engineering, machine learning, or data science, with 2+ years in AI systems development.
- 5+ years of engineering leadership experience, including leading, mentoring, and scaling high-performing technical or AI/ML teams.
- Proven experience delivering LLM-powered applications and AI/ML systems into production at enterprise scale.
- Deep understanding of AI supporting infrastructure, security, testing, and monitoring/maintenance pipelines.
- Strong knowledge of Python, with hands-on experience with AI/ML-relevant packages and tools, such as NumPy, Pandas, SciPy, and Scikit-learn.
- Deep experience with modern LLM ecosystems and tools, such as:
- OpenAI / Anthropic / Google / open-source LLMs / other
- Claude Code, Codex, Cursor, GitHub Copilot, or similar
- LangChain, LlamaIndex, Crewai, or similar orchestration frameworks
- Experience building RAG pipelines, working with vector databases, and integrating AI with enterprise data and application environments.
- Experience designing and integrating APIs, MCP servers, scalable backend services, and AI platform components.
- Strong understanding of prompt engineering, embeddings, model evaluation, fine-tuning, and agent design and orchestration.
- Experience with cloud-based AI infrastructure and modern software delivery practices across AWS, Azure, or GCP. Familiarity with SnowFlake is preferred.
- Experience with MLOps / LLMOps, evaluation frameworks, observability, and continuous improvement for AI systems in production.
- Strong understanding of AI governance, security, privacy, risk controls, and compliance in enterprise or regulated environments.
- Experience influencing cross-functional stakeholders and communicating effectively with senior technology and business leaders.
- Ability to balance hands-on technical depth with strategic leadership, organizational development, and execution discipline.
Preferred Qualifications
- Advanced degree (M.Sc. or Ph.D.) in a relevant field.
- Experience building AI agents, agentic platforms, or autonomous workflows in production.
- Experience leading senior engineers, or technical leads in a scaled engineering organization.
- Familiarity with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, OpenAI Agents SDK, Semantic Kernel, LlamaIndex, Frontier, or similar.
- Experience with fine-tuning LLMs or parameter-efficient fine-tuning (PEFT) methods such as LoRA, or similar.
- Experience with multi-modal AI, document processing, semantic search, knowledge assistants, and enterprise workflow automation.
- Familiarity with Java, JavaScript, and enterprise application environments.
- Experience with vendor management, budgeting, and buy-vs-build evaluation for AI platforms and tooling.
- Experience implementing responsible AI, governance frameworks, security, observability, and guardrails at scale.
- Experience leading AI transformation initiatives across large, matrixed organizations.
- Experience in the insurance industry, finance, or other regulated industries, with exposure to fraud detection, risk analysis, claims, underwriting, servicing customers, or document intelligence.
What We Offer
- Opportunity to shape the future of AI engineering in the insurance industry
- Leadership role building next-generation Generative and Agentic AI capabilities
- High-impact work across customer, employee, and operational experiences
- Collaborative environment with technology, data, and business leaders
- Competitive compensation and benefits
- Hybrid work environment in Boston
- Opportunity to build both enterprise AI platforms and high-value AI products that drive measurable business results
Impact
In this key role, you will shape how AI is engineered, governed, and scaled across the enterprise. You will help build an AI-first insurance company, leveraging Generative and Agentic AI to improve decision-making, streamline operations, accelerate service, and deliver better experiences for customers, business stakeholders.
Salary Range:
The pay range for this position is $205,000 to $282,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
Perks and Benefits:
- 4 weeks accrued paid time off + 9 paid national holidays per year
- Free onsite gym at our Boston Location
- Tuition Reimbursement
- Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision)
- Robust health and wellness program and fitness reimbursements
- Auto and home insurance discounts
- Matching gift opportunities
- Annual 401(k) Employer Contribution (up to 7.5% of your base salary)
- Various Paid Family leave options including Paid Parental Leave
- Resources to promote Professional Development (LinkedIn Learning and licensure assistance)
- Convenient location directly across from South Station and Pre-Tax Commuter Benefits
About the Company
The Plymouth Rock Company and its affiliated group of companies write and manage over $2.3 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
We are seeking a strategic and hands-on Director, AI Engineering to lead the design, development, and scaling of Generative and Agentic AI systems that transform how our company operates and serves customers. This role focuses on building AI applications and reusable AI platform capabilities powered by large language models (LLMs), retrieval-augmented generation (RAG), Model Context Protocol (MCP), multi-agent systems, Agentic AI platforms, and modern AI/ML infrastructure across the enterprise for both internal and customer-facing use cases.
The ideal candidate combines deep expertise in a modern AI/ML stack with strong AI software engineering fundamentals, strong people leadership, and the ability to partner effectively across technology, data, product, operations, and business teams.
You will help define the AI engineering strategy and roadmap, lead a high-performing AI Engineering team, build and manage scalable AI products, establish standards for scalable and secure AI delivery, and help translate AI investments into measurable business outcomes.
Key Responsibilities
- Help to define and lead the execution of AI engineering strategy, target architecture, and roadmap for Generative and Agentic AI across the enterprise.
- Manage and motivate a high-performing team of AI engineers including coaching, mentoring, and scaling as required.
- Design, build, and oversee deployment of scalable LLM-powered applications and AI-native products for customer support, business operations, and internal productivity.
- Lead the development of AI agents, agentic platforms, and autonomous workflows capable of reasoning, planning, and executing multi-step tasks.
- Implement RAG architectures and pipelines to leverage proprietary data, internal knowledge bases, enterprise systems, and structured/unstructured content.
- Stand-up and evolve MCP servers, tool integrations, and multi-connectivity AI platforms to support secure orchestration across internal and external systems.
- Establish and oversee standards for prompt design, model evaluation, guardrails, observability, testing, and production readiness to ensure accuracy, resiliency, security, and regulatory compliance.
- Lead the design of MLOps and LLMOps pipelines for model lifecycle management, monitoring, continuous evaluation, and improvement.
- Leverage CI/CD and Agile methodologies for AI product development.
- Partner with architecture, security, legal, compliance, and data teams to ensure AI solutions meet requirements for privacy, governance, auditability, and responsible AI.
- Drive build vs. buy decisions, vendor selection, and collaboration with external partners, consultants, and internal teams to deliver scalable, high-quality AI solutions.
- Work closely with business leaders to identify and prioritize high-value use cases across the insurance business, process optimization, software development, and employee productivity.
- Define and track success metrics for adoption, quality, reliability, business impact, cost efficiency, and delivery velocity.
- Stay current with emerging advancements in AI/ML, Generative AI, agentic frameworks, model architectures, and enterprise AI engineering practices.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Applied Mathematics, or a related field. Graduate degrees are preferred, but not necessary.
- 10+ years of experience in software engineering, platform engineering, machine learning, or data science, with 2+ years in AI systems development.
- 5+ years of engineering leadership experience, including leading, mentoring, and scaling high-performing technical or AI/ML teams.
- Proven experience delivering LLM-powered applications and AI/ML systems into production at enterprise scale.
- Deep understanding of AI supporting infrastructure, security, testing, and monitoring/maintenance pipelines.
- Strong knowledge of Python, with hands-on experience with AI/ML-relevant packages and tools, such as NumPy, Pandas, SciPy, and Scikit-learn.
- Deep experience with modern LLM ecosystems and tools, such as:
- OpenAI / Anthropic / Google / open-source LLMs / other
- Claude Code, Codex, Cursor, GitHub Copilot, or similar
- LangChain, LlamaIndex, Crewai, or similar orchestration frameworks
- Experience building RAG pipelines, working with vector databases, and integrating AI with enterprise data and application environments.
- Experience designing and integrating APIs, MCP servers, scalable backend services, and AI platform components.
- Strong understanding of prompt engineering, embeddings, model evaluation, fine-tuning, and agent design and orchestration.
- Experience with cloud-based AI infrastructure and modern software delivery practices across AWS, Azure, or GCP. Familiarity with SnowFlake is preferred.
- Experience with MLOps / LLMOps, evaluation frameworks, observability, and continuous improvement for AI systems in production.
- Strong understanding of AI governance, security, privacy, risk controls, and compliance in enterprise or regulated environments.
- Experience influencing cross-functional stakeholders and communicating effectively with senior technology and business leaders.
- Ability to balance hands-on technical depth with strategic leadership, organizational development, and execution discipline.
Preferred Qualifications
- Advanced degree (M.Sc. or Ph.D.) in a relevant field.
- Experience building AI agents, agentic platforms, or autonomous workflows in production.
- Experience leading senior engineers, or technical leads in a scaled engineering organization.
- Familiarity with agentic frameworks such as LangChain, LangGraph, AutoGen, CrewAI, OpenAI Agents SDK, Semantic Kernel, LlamaIndex, Frontier, or similar.
- Experience with fine-tuning LLMs or parameter-efficient fine-tuning (PEFT) methods such as LoRA, or similar.
- Experience with multi-modal AI, document processing, semantic search, knowledge assistants, and enterprise workflow automation.
- Familiarity with Java, JavaScript, and enterprise application environments.
- Experience with vendor management, budgeting, and buy-vs-build evaluation for AI platforms and tooling.
- Experience implementing responsible AI, governance frameworks, security, observability, and guardrails at scale.
- Experience leading AI transformation initiatives across large, matrixed organizations.
- Experience in the insurance industry, finance, or other regulated industries, with exposure to fraud detection, risk analysis, claims, underwriting, servicing customers, or document intelligence.
What We Offer
- Opportunity to shape the future of AI engineering in the insurance industry
- Leadership role building next-generation Generative and Agentic AI capabilities
- High-impact work across customer, employee, and operational experiences
- Collaborative environment with technology, data, and business leaders
- Competitive compensation and benefits
- Hybrid work environment in Boston
- Opportunity to build both enterprise AI platforms and high-value AI products that drive measurable business results
Impact
In this key role, you will shape how AI is engineered, governed, and scaled across the enterprise. You will help build an AI-first insurance company, leveraging Generative and Agentic AI to improve decision-making, streamline operations, accelerate service, and deliver better experiences for customers, business stakeholders.
Salary Range:
The pay range for this position is $205,000 to $282,000 annually. Actual compensation will vary based on multiple factors, including employee knowledge and experience, role scope, business needs, geographical location, and internal equity.
Perks and Benefits:
- 4 weeks accrued paid time off + 9 paid national holidays per year
- Free onsite gym at our Boston Location
- Tuition Reimbursement
- Low cost and excellent coverage health insurance options that start on Day 1 (medical, dental, vision)
- Robust health and wellness program and fitness reimbursements
- Auto and home insurance discounts
- Matching gift opportunities
- Annual 401(k) Employer Contribution (up to 7.5% of your base salary)
- Various Paid Family leave options including Paid Parental Leave
- Resources to promote Professional Development (LinkedIn Learning and licensure assistance)
- Convenient location directly across from South Station and Pre-Tax Commuter Benefits
About the Company
The Plymouth Rock Company and its affiliated group of companies write and manage over $2.3 billion in personal and commercial auto and homeowner's insurance throughout the Northeast and mid-Atlantic, where we have built an unparalleled reputation for service. We continuously invest in technology, our employees thrive in our empowering environment, and our customers are among the most loyal in the industry. The Plymouth Rock group of companies employs more than 1,900 people and is headquartered in Boston, Massachusetts. Plymouth Rock Assurance Corporation holds an A.M. Best rating of “A-/Excellent”
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Get Access To All JobsTips for Finding Green Card Sponsorship as an AI Data Specialist
Frame your credentials for PERM documentation
Your degree field matters more than your job title during PERM. A computer science, statistics, or data science degree maps cleanly to AI Data Specialist duties. If your degree is in a different field, document how your coursework and experience align to the role's technical requirements.
Target employers with active EB-2 and EB-3 filing histories
Use the OFLC Wage Search to identify employers who have filed PERM applications for AI and data roles. Employers with repeated filings have established internal processes, which shortens the timeline between your offer and the start of your green card petition.
Search AI Data Specialist jobs on Migrate Mate
Migrate Mate filters job listings by green card sponsorship history, so you're only seeing employers who have sponsored EB-2 or EB-3 petitions for data roles before. Use it to narrow your search before applying broadly.
Clarify the job description before PERM is filed
The PERM labor certification locks in the job duties that must remain consistent through your I-140 and adjustment of status. If your AI Data Specialist role evolves significantly, USCIS may treat the change as a new position, restarting the process.
Understand how DOL prevailing wage affects your offer
Before PERM is filed, DOL must assign a prevailing wage for your specific role and location. Employers are required to pay at or above that wage. Verify the wage level assigned to your position matches the actual duties you'll perform, not a lower-complexity data entry classification.
Use O*NET to align your resume with PERM requirements
The O*NET occupation profile for AI and data roles lists the tasks, tools, and knowledge areas DOL expects the position to reflect. Aligning your resume language to O*NET descriptors reduces the risk of a PERM audit challenging the job's specialty occupation classification.
Green Card AI Data Specialist: Frequently Asked Questions
Does an AI Data Specialist role qualify for EB-2 or EB-3 sponsorship?
Most AI Data Specialist positions qualify under EB-3 as skilled workers requiring a bachelor's degree, and many qualify under EB-2 if the role requires an advanced degree or the employer can demonstrate the position requires work above the norm. Roles involving machine learning model evaluation, data pipeline architecture, or AI system quality assurance tend to support EB-2 filings more readily than general data labeling positions.
How does PERM green card sponsorship differ from H-1B for AI Data Specialist roles?
H-1B visa sponsorship is temporary and subject to an annual lottery cap, while PERM-based green card sponsorship is permanent and has no lottery. The PERM process requires your employer to conduct a formal recruitment test showing no qualified U.S. worker applied, which adds time upfront but leads to lawful permanent residency. For nationals from countries without long EB-3 backlogs, the total timeline from PERM filing to a green card can be comparable to multiple H-1B cycles.
Which employers are most likely to sponsor green cards for AI Data Specialist roles?
Employers with established AI, machine learning, or data infrastructure teams are the most consistent green card sponsors for this role. You can identify them by searching the OFLC Wage Search for PERM filings under data and AI job codes. Migrate Mate surfaces these employers directly by filtering job listings based on verified green card sponsorship history, so you can focus your search on companies already familiar with the EB-2 and EB-3 process.
Can I change jobs after my employer files the PERM application?
Changing employers before your I-140 petition is approved generally requires restarting the PERM process with your new employer. Once your I-140 is approved and you've been in the queue for more than 180 days, portability rules under AC21 allow you to change to a similar role without losing your priority date. For AI Data Specialist positions, the new role must be in the same or a substantially similar occupational classification.
What documentation should I prepare before my employer starts the PERM process?
Gather official transcripts showing your degree field, any credential evaluations if your degree is from outside the U.S., employment verification letters for prior roles, and documentation of specialized training or certifications related to AI systems or data infrastructure. PERM audits often focus on whether the foreign worker meets the minimum requirements listed in the job posting, so your documentation should directly address each stated requirement in the position description.