AI Engineer Jobs in USA with Visa Sponsorship
AI engineers who specialize in taking models from research prototypes to production-grade systems are in surging demand across US companies scaling their AI capabilities. Unlike research-focused roles, AI engineering emphasizes MLOps, model serving, and building reliable inference pipelines - skills that are scarce and highly valued by employers filing sponsorship petitions. If you can bridge the gap between a trained model and a product that serves millions of users, US companies will sponsor your visa to do exactly that.
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Get Access To All JobsINTRODUCTION
Piper Companies is seeking a Lead AI Engineer to support a rapidly growing organization in the insurance technology industry. The Lead AI Engineer role is ideal for an engineer who combines strong full stack development experience with hands-on work delivering real-world Generative AI solutions in production.
ROLE AND RESPONSIBILITIES
The Lead AI Engineer role requires you to sit on site 3 days per week in Durham, NC.
- Partner with technology leadership to stand up and scale a new AI-focused group, from defining use cases through launch of production solutions.
- Design and implement end-to-end AI features, including data pipelines, MCP/RAG workflows, model training/testing, and deployment into web and mobile applications.
- Embed Generative AI and, over time, agentic capabilities into existing digital customer and employee experiences.
- Collaborate with product, data, security, and engineering teams to ensure AI solutions are robust, secure, and aligned with business goals.
BASIC QUALIFICATIONS
- Bachelor of Science in Computer Science or related field is required
- 3–5 years of full stack engineering experience, ideally with JavaScript/TypeScript, modern web frameworks, and AWS cloud services.
- 1–2 years of deep, hands-on AI experience, having moved into AI-focused roles or projects delivering LLM/Generative AI solutions.
- Practical experience setting up data pipelines, implementing MCP/RAG architectures, and integrating Generative AI into mobile and web experiences that have shipped to production.
- Background spanning architecture design, data onboarding, training and evaluation of models, and deployment of scalable APIs and front-end integrations.
- Strong communication skills, ability to translate requirements into technical designs, and comfort working in a fast-paced, product-driven environment.
COMPENSATION
- $155,000 - $195,000 base salary
- Full Comprehensive Benefits: Health, Vision, Dental, PTO, Paid Holiday and Sick Leave if Required by Law.
This job opens for applications on 2/27/2026. Applications for this job will be accepted for at least 30 days from the posting date.
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How to Get Visa Sponsorship as an AI Engineer
Position yourself at the intersection of AI and engineering
AI Engineer is a fast-growing title that bridges ML research and production software. Highlight experience deploying models, building RAG pipelines, or integrating LLMs into products - these applied skills are what companies are hiring for.
Target companies actively building AI engineering teams
Companies from startups to enterprises are creating new AI engineering roles and sponsoring H-1B petitions to fill them. Databricks, Notion, Figma, and similar companies have expanded AI headcount specifically because demand outpaces domestic supply.
Clarify your SOC code with your employer
AI Engineer roles can file under SOC 15-1252 (Software Developers) if engineering-focused or 15-2051 (Data Scientists) if research-heavy. The right choice depends on your day-to-day duties - work with your employer's immigration attorney to match accurately.
Use STEM OPT to build production AI experience
A STEM-eligible degree gives you up to 3 years of work authorization through OPT. Ship real AI features during that time - companies are far more likely to sponsor an engineer who already knows their codebase and deployment stack.
Differentiate yourself with full-stack AI skills
Many AI engineers can fine-tune models but struggle with production infrastructure. Expertise in model serving, API design, latency optimization, and monitoring makes you harder to replace and gives employers a stronger reason to sponsor.
Consider the O-1 path if you have notable AI work
Significant open-source contributions, widely used AI tools, or media coverage of your work can support an O-1 extraordinary ability petition. You don't need a PhD - demonstrated impact in applied AI can qualify.
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Get Access To All JobsFrequently Asked Questions
What is the difference between an AI engineer and a machine learning engineer for visa sponsorship purposes?
For immigration purposes, the distinction matters less than how the employer describes the role in the petition. AI engineer roles tend to emphasize building end-to-end AI-powered products, integrating LLMs, and designing retrieval-augmented generation systems. ML engineer roles focus more on model training infrastructure and serving pipelines. Both qualify as specialty occupations, and the key is specificity in the job description listing the technical skills required and the degree fields that prepare someone for the work.
How important is production experience versus research experience for AI engineer visa sponsorship?
Production experience is the differentiator for AI engineering roles. Employers sponsoring AI engineers are specifically looking for someone who can deploy and maintain AI systems in production, handling model versioning, building evaluation frameworks, and optimizing inference costs. While research experience shows technical depth, the visa petition for an AI engineer role will emphasize production engineering requirements. Highlight systems you have built and shipped, along with experience in tools like Kubernetes, Docker, and model serving frameworks.
Do I need a master's degree or PhD to get sponsored as an AI engineer?
A bachelor's degree in computer science or a related field is sufficient for most AI engineering positions. Unlike AI research roles where a PhD is often expected, AI engineering emphasizes practical systems-building skills over academic credentials. That said, a master's degree qualifies you for the additional 20,000 H-1B lottery slots reserved for advanced degree holders and signals deeper technical knowledge. Many successful AI engineer petitions are filed with bachelor's-level candidates who have strong production ML experience.
Which companies are most actively sponsoring AI engineers?
Companies scaling AI products are the most active sponsors. This includes large tech firms (Google, Meta, Amazon, Microsoft), AI-first startups (OpenAI, Anthropic, Cohere), and AI infrastructure companies (Databricks, Anyscale, Weights & Biases). Enterprise companies integrating AI into their products across healthcare, finance, and e-commerce are also growing sponsors. Look for employers whose job descriptions specifically mention LLM integration, RAG systems, or production AI deployment, as these roles are distinct enough to produce strong petitions.
What technical skills should I emphasize in an AI engineer visa petition?
Focus on skills that distinguish AI engineering from general software development. LLM integration, vector database management, prompt engineering pipelines, inference optimization, and retrieval-augmented generation architecture are the most relevant. Experience with evaluation frameworks for AI systems, cost optimization for GPU workloads, and monitoring for model quality in production also carries weight. The more specific the technical requirements in the petition, the stronger the specialty occupation argument.
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