Green Card Genai Engineer Jobs
GenAI Engineer roles qualify for green card sponsorship under EB-2 and EB-3, with employers filing PERM labor certifications through DOL before petitioning USCIS. Your advanced degree in computer science, AI, or a related field strengthens an EB-2 classification, while hands-on LLM and model deployment experience supports the specialty occupation requirement throughout the sponsorship process.
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Get Access To All JobsINTRODUCTION
Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
ROLE
GenAI Architect
Location:
Iselin, NJ (Hybrid mode - Orion office)
Project Overview:
Join our dynamic Delivery department as a GenAI Architect, where you will play a key role in designing and implementing innovative solutions leveraging Generative AI, AI Architecture, and Transformation methodologies. With a focus on cutting-edge technologies like Azure and MCP, you will help shape robust AI-driven solutions for enterprise applications.
Modernization, quality engineering, DevSecOps, and SRE.
Partnering with client executives, sector leaders, and delivery teams, you will translate AI strategy into production solutions and measurable business outcomes. Candidates must have personally designed, coded, and deployed production AI systems.
Key Responsibilities:
- Lead AI adoption: Co-create roadmaps aligned to client priorities; prioritize high-impact use cases and embed AI into end-to-end delivery workflows.
- Architect and build solutions: Design production-grade LLM applications and multi-agent systems with secure enterprise integrations, governed model access, and clear trade-offs across quality, latency, cost, and risk.
- Drive hands-on execution: Build rapid client PoCs, guide production deployment, debug agent behavior, review code, and establish reusable architectures and engineering standards.
- Design and architect Generative AI solutions tailored to enterprise needs, ensuring scalability and reliability.
- Lead the integration of AI-related technologies within existing enterprise architecture frameworks.
- Drive digital transformation initiatives by leveraging Agentic AI and innovative methodologies.
- Develop and implement APIs to support seamless integration of AI-powered solutions across platforms.
- Collaborate with cross-functional teams to define and refine solution architectures.
- Ensure compliance with best practices and standards for enterprise and solution architecture.
- Stay updated on emerging AI trends and technologies to incorporate them into architectural strategy.
- Lead clients and teams: Advise senior stakeholders, enable changes in skills and ways of working, and lead forward-deployed engineers (FDEs) and AI specialists. Develop reusable assets, industry perspectives, and thought leadership.
- Embed responsible AI: Establish security, privacy, data residency, auditability, and human oversight controls appropriate to client and regulatory requirements.
BASIC QUALIFICATIONS
Required Skills and Experience:
- Mandatory:
- Proven AI transformation experience, including recent, personal delivery of production LLM applications and agents, preferably in regulated or security-sensitive environments.
- Deep AI architecture expertise spanning model selection, orchestration, data and context layers, identity, integration, and observability.
- Hands-on experience with multi-agent systems and Agent-to-Agent (A2A) interoperability, Model Context Protocol (MCP) servers and clients, and AI gateways for routing, access controls, guardrails, and cost governance.
- Strong practical knowledge of RAG, GraphRAG, context engineering, agent memory, and agent frameworks or SDKs; experience applying AI coding assistants and autonomous agents across the SDLC.
- Expertise in LLMOps, evaluation, regression testing, tracing, production monitoring, model adaptation, and inference optimization.
- Experience implementing defenses against prompt injection and tool misuse, human approval controls, and responsible AI governance.
- Hands-on experience with at least one major cloud AI platform—Azure AI Foundry, AWS Bedrock, or Google Vertex AI—and leading model-provider APIs.
- Strong executive communication, team leadership, and commercial judgment, with the ability to translate complex technology into compelling business value.
Success in This Role
Secure, scalable AI adoption that moves beyond experimentation, delivers measurable engineering and business improvements, and maintains continuity from strategy and deal commitments through production execution.
AI Tools -
- Azure AI Foundry
- Agent365
- Copilot
- MS Purview
- Defender
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, "Orion," "we" or "us") are committed to protecting your privacy. This Candidate Privacy Policy ("Notice") explains:
- What information we collect during our application and recruitment process and why we collect it;
- How we handle that information; and
- How to access and update that information.
Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
INTRODUCTION
Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education.
ROLE
GenAI Architect
Location:
Iselin, NJ (Hybrid mode - Orion office)
Project Overview:
Join our dynamic Delivery department as a GenAI Architect, where you will play a key role in designing and implementing innovative solutions leveraging Generative AI, AI Architecture, and Transformation methodologies. With a focus on cutting-edge technologies like Azure and MCP, you will help shape robust AI-driven solutions for enterprise applications.
Modernization, quality engineering, DevSecOps, and SRE.
Partnering with client executives, sector leaders, and delivery teams, you will translate AI strategy into production solutions and measurable business outcomes. Candidates must have personally designed, coded, and deployed production AI systems.
Key Responsibilities:
- Lead AI adoption: Co-create roadmaps aligned to client priorities; prioritize high-impact use cases and embed AI into end-to-end delivery workflows.
- Architect and build solutions: Design production-grade LLM applications and multi-agent systems with secure enterprise integrations, governed model access, and clear trade-offs across quality, latency, cost, and risk.
- Drive hands-on execution: Build rapid client PoCs, guide production deployment, debug agent behavior, review code, and establish reusable architectures and engineering standards.
- Design and architect Generative AI solutions tailored to enterprise needs, ensuring scalability and reliability.
- Lead the integration of AI-related technologies within existing enterprise architecture frameworks.
- Drive digital transformation initiatives by leveraging Agentic AI and innovative methodologies.
- Develop and implement APIs to support seamless integration of AI-powered solutions across platforms.
- Collaborate with cross-functional teams to define and refine solution architectures.
- Ensure compliance with best practices and standards for enterprise and solution architecture.
- Stay updated on emerging AI trends and technologies to incorporate them into architectural strategy.
- Lead clients and teams: Advise senior stakeholders, enable changes in skills and ways of working, and lead forward-deployed engineers (FDEs) and AI specialists. Develop reusable assets, industry perspectives, and thought leadership.
- Embed responsible AI: Establish security, privacy, data residency, auditability, and human oversight controls appropriate to client and regulatory requirements.
BASIC QUALIFICATIONS
Required Skills and Experience:
- Mandatory:
- Proven AI transformation experience, including recent, personal delivery of production LLM applications and agents, preferably in regulated or security-sensitive environments.
- Deep AI architecture expertise spanning model selection, orchestration, data and context layers, identity, integration, and observability.
- Hands-on experience with multi-agent systems and Agent-to-Agent (A2A) interoperability, Model Context Protocol (MCP) servers and clients, and AI gateways for routing, access controls, guardrails, and cost governance.
- Strong practical knowledge of RAG, GraphRAG, context engineering, agent memory, and agent frameworks or SDKs; experience applying AI coding assistants and autonomous agents across the SDLC.
- Expertise in LLMOps, evaluation, regression testing, tracing, production monitoring, model adaptation, and inference optimization.
- Experience implementing defenses against prompt injection and tool misuse, human approval controls, and responsible AI governance.
- Hands-on experience with at least one major cloud AI platform—Azure AI Foundry, AWS Bedrock, or Google Vertex AI—and leading model-provider APIs.
- Strong executive communication, team leadership, and commercial judgment, with the ability to translate complex technology into compelling business value.
Success in This Role
Secure, scalable AI adoption that moves beyond experimentation, delivers measurable engineering and business improvements, and maintains continuity from strategy and deal commitments through production execution.
AI Tools -
- Azure AI Foundry
- Agent365
- Copilot
- MS Purview
- Defender
Orion is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, citizenship status, disability status, genetic information, protected veteran status, or any other characteristic protected by law.
Candidate Privacy Policy
Orion Systems Integrators, LLC and its subsidiaries and its affiliates (collectively, "Orion," "we" or "us") are committed to protecting your privacy. This Candidate Privacy Policy ("Notice") explains:
- What information we collect during our application and recruitment process and why we collect it;
- How we handle that information; and
- How to access and update that information.
Your use of Orion services is governed by any applicable terms in this notice and our general Privacy Policy.
See all 39+ Green Card Genai Engineer Jobs
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Get Access To All JobsTips for Finding Green Card Sponsorship as a Genai Engineer
Document your AI specialization before applying
Gather performance reviews, published model benchmarks, and project documentation that tie your work directly to LLM architecture, fine-tuning pipelines, or RAG systems. PERM audits scrutinize whether your credentials match the posted job requirements, so specificity here prevents delays.
Search employers with active PERM filings
Use Migrate Mate to filter GenAI Engineer roles by employers who have filed PERM labor certifications, so you're targeting companies already familiar with the DOL process rather than educating a hiring team from scratch.
Identify whether EB-2 or EB-3 fits your profile
EB-2 requires a master's degree or equivalent in a directly related field, while EB-3 covers bachelor's-level professionals. If your degree is in a tangentially related discipline, prepare a credential evaluation and a skills-to-role mapping letter before interviews start.
Ask about priority date strategy during offer negotiations
For candidates born in high-backlog countries, an employer willing to file an EB-2 and a concurrent EB-3 petition gives you two priority dates to track. Clarify whether the employer's immigration counsel handles this dual-filing approach before you sign.
Verify the job description matches OFLC prevailing-wage data
Employers set the PERM wage floor using the OFLC Wage Search. If your offer letter lists a Level I or Level II wage for a role that DOL classifies at Level III, the labor certification is at risk, so confirm wage level alignment before PERM is filed.
Confirm the employer understands specialty occupation requirements
USCIS requires that GenAI Engineer roles normally demand at least a bachelor's degree in a specific specialty. Use O*NET occupation data and your employer's actual job requirements to build a strong specialty occupation argument during the I-140 petition stage.
Green Card Genai Engineer: Frequently Asked Questions
Does a GenAI Engineer role qualify as a specialty occupation for green card purposes?
Yes. USCIS evaluates whether the position normally requires at least a bachelor's degree in a specific field such as computer science, artificial intelligence, or machine learning. GenAI Engineer roles that involve LLM architecture, model fine-tuning, or inference optimization consistently meet that standard, though the employer must document the degree requirement clearly in the PERM job description.
How does PERM green card sponsorship differ from H-1B sponsorship for GenAI Engineers?
H-1B visa is a temporary status renewed in three-year increments with no path to permanence on its own, while PERM is the first step toward lawful permanent residency. EB-3 green cards for GenAI Engineers have no annual per-person cap, so unlike H-1B, there is no lottery. The tradeoff is timeline: PERM labor certification alone takes six to eighteen months before the I-140 petition stage begins.
What makes a GenAI Engineer profile stronger for EB-2 versus EB-3 classification?
EB-2 requires a master's degree or a bachelor's degree plus five years of progressive experience in a directly related specialty. Candidates whose work focuses on foundational model research, novel training techniques, or published AI benchmarks tend to support EB-2 arguments more easily. EB-3 is the practical fallback for candidates with a bachelor's degree and strong deployment or MLOps experience but without the graduate credential.
How can I find GenAI Engineer employers who are already willing to sponsor green cards?
Migrate Mate lets you search GenAI Engineer roles filtered by employers with verified PERM filing history, so you avoid companies that would need to start the green card process from zero. Targeting employers with prior PERM experience shortens the education phase and reduces the risk that sponsorship falls apart after an offer is extended.
Can my employer start PERM while I'm on an H-1B for a GenAI Engineer role?
Yes, and starting early is strategically important. PERM can be filed at any point during H-1B status, and having an approved I-140 petition before your sixth year of H-1B allows extensions beyond the standard six-year cap under AC21 portability rules. Many GenAI Engineers in high-backlog countries rely on this overlap to maintain lawful status while their priority date becomes current.