AI Specialist Jobs in USA with Visa Sponsorship
AI Specialist roles are among the most actively sponsored positions in the U.S. right now, with H-1B visa approval rates for software and AI-related occupations consistently above 85%. Employers across tech, finance, and healthcare are filing petitions year-round, and cap-exempt employers offer paths outside the lottery. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsINTRODUCTION
Groupon is a marketplace where customers discover new experiences and services every day and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis. Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.
ABOUT THE ROLE
Most roles at the start of a career come with an onboarding deck and a defined task list. This one does not. Groupon is rebuilding how it sells — from the ground up, with AI — and the person in this role is part of that build from day one. The vehicle is Project Foundry: a production fleet of AI agents designed to give Groupon a parallel sales force that operates 24/7 and to make every human rep sharper the moment they step into a deal. Two layers: the first runs full sales motions autonomously — outbound, inbound triage, reactivation — so reps receive warm opportunities rather than cold lists. The second equips reps at the handoff point — context surfaced, deal history ready, next action suggested. Reporting directly to the CSO, the GTM AI Specialist learns the full architecture, contributes to both layers, and progressively takes end-to-end ownership of agents in production. You are not joining a team that advises the business on AI. You are building the system that is the business. There is no playbook. You help write it.
North Star
Ship AI agents that run on real merchant data, prove their value in measurable terms, and make the sales organization faster and sharper than it would be without them. The build compounds — every signal, every call, every conversion feeds back into what you build next. You are here to make that happen.
WHAT YOU’LL DO:
- Build across both layers of the fleet — Layer 1: agents that run autonomously without rep involvement — outbound sequencing, lead prioritization, inbound triage, reactivation. Reps receive warm opportunities, not cold lists. Layer 2: agents that equip reps at the moment they step in — account context surfaced, deal history ready, next action suggested. You learn how both layers work and progressively contribute to each.
- Identify what to build and make the case for it — You are not waiting to be given a task list. You look at the sales organization, find the highest-value problem an agent could solve, and bring a structured proposal to the CSO. Judgment about what is worth building matters as much as the ability to build it.
- Test, measure, and iterate — You run experiments on real merchant data, measure whether what you built is working, identify failure modes, and refine. Every agent you touch has a documented performance trail. You do not ship and move on.
- Mine call transcripts for agent inputs — Process sales call recordings to extract patterns, category signals, and performance data. This is raw material for the agents you build — not a separate analytics workstream. You surface insights from it and design around them.
- Document and maintain what you ship — Every agent you deploy has a before/after record. You keep it current. You present it. You own what you built — not just while you're building it.
WHAT YOU BRING:
- A degree from an Ivy League or equivalent top-tier university strongly preferred— computer science, data science, economics, mathematics, or a field that taught you to think in systems. The subject matters less than the rigor of how you were trained to think.
- You have built an AI agent or automated workflow — not a class project. Something you designed, built, and iterated on because you wanted to see if it would work. You can explain what it did, what broke, and what you changed. The bar is not commercial success. The bar is that you shipped something real.
- Technical capability to build: you have used LLM APIs (OpenAI, Anthropic, or equivalent), built prompt architectures, and connected systems together. Python or equivalent. You do not need to be a software engineer — but you need to be able to build a working agent without asking someone else to write the code.
- Commercial curiosity. You read about how businesses make money. You ask why something converts and why something else doesn’t. You do not need a sales background — you need the instinct to connect what you build to a GP outcome.
- Rigor with data. You do not accept a number without understanding where it came from. You build your own measurement frameworks when none exist.
WHO YOU ARE:
- Builder first — your instinct is to build, not to ask for permission. You have side projects because you were curious, not because someone assigned them.
- AI-native, not AI-curious — you have spent real time understanding what these systems can and cannot do. You know the difference between a demo and a deployed agent.
- Comfortable with ambiguity — you can start without a complete brief, identify the next right step, and keep moving. You learn faster by doing than by waiting for clarity.
- Commercially curious — you connect what you build to a business outcome. You ask why something converts and why something doesn’t. Technology is the means; impact is the goal.
- You are early in your career. That is the point. If you don’t tick every box but you build, learn fast, and want to work on something that doesn’t yet exist — we want to hear from you.
HOW WE OPERATE:
Five principles. Non-negotiable.
- Extreme Ownership — if an agent you’re responsible for underperforms, you own the diagnosis and the fix — not the vendor, not the backlog.
- Speed Over Comfort — you ship an experiment before you’re sure it will work. You learn from live data, not from waiting.
- Impact Obsessed — every hour of your time should connect to a GP outcome — directly or as a clear step toward one.
- Simplify to Scale — you document what you build so it can be used by someone else. Complexity you create and don’t explain is debt.
- Disciplined — you keep your data clean, your experiments rigorous, and your performance logs current. Good intentions without rigour produce noise.
HOW WE MEASURE YOUR SUCCESS:
- Agent shipped: first working agent in production by day 90, with a documented hypothesis, performance data, and an honest assessment of what worked and what didn’t
- Quality of proposals: structured agent proposals to the CSO — ranked by commercial impact, grounded in data, specific about what gets built and how it gets measured
- Experiment rigour: every agent you deploy has a defined success metric set before go-live — not retrofitted afterward
- Learning progression: demonstrated improvement in AI build quality, commercial reasoning, and stack fluency quarter over quarter — assessed directly by the CSO
- Contribution to the fleet: at least one documented insight per month surfaced from call transcripts or agent performance data — standalone, with a recommendation
THE DETAILS:
- Location: Downtown Chicago (hybrid, 3 days a week in-office) + Alternate locations: Can be remote for the right fit
- Salary Range: $70,000 – $110,000 (depending on experience), plus eligibility to participate in a performance-based bonus program.
- Benefits: Medical, dental, vision, EAP, 401(k) match, ESPP, life and disability insurance, FSAs, flexible PTO, and more.
Groupon is an AI-First Company
We’re committed to building smarter, faster, and more innovative ways of working—and AI plays a key role in how we get there. We encourage candidates to leverage AI tools during the hiring process where it adds value, and we’re always keen to hear how technology improves the way you work. If you’re passionate about AI or curious to explore how it can elevate your role— you’ll be right at home here. Groupon’s purpose is to build strong communities through thriving small businesses. To learn more about the world’s largest local e-commerce marketplace, click here. You can also find out more about us in the latest Groupon news as well as learning about our DEI approach. If all of this sounds like something that’s a great fit for you, then click apply and join us on a mission to become the ultimate destination for local experiences and services.
Beware of Recruitment Fraud:
Groupon follows a merit-based recruitment process without charging job seekers any fees. We've noticed an increase in recruitment fraud, including fake job postings and fraudulent interviews and job offers aimed at stealing personal information or money. Be cautious of individuals falsely representing Groupon's Talent Acquisition team with fake job offers. If you encounter any suspicious job offers or interview calls demanding money, recognize these as scams. Groupon is not responsible for losses from such dealings. For legitimate job openings (and a sneak peek into life at Groupon), always check our official career website at Groupon Careers.
INTRODUCTION
Groupon is a marketplace where customers discover new experiences and services every day and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis. Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact.
ABOUT THE ROLE
Most roles at the start of a career come with an onboarding deck and a defined task list. This one does not. Groupon is rebuilding how it sells — from the ground up, with AI — and the person in this role is part of that build from day one. The vehicle is Project Foundry: a production fleet of AI agents designed to give Groupon a parallel sales force that operates 24/7 and to make every human rep sharper the moment they step into a deal. Two layers: the first runs full sales motions autonomously — outbound, inbound triage, reactivation — so reps receive warm opportunities rather than cold lists. The second equips reps at the handoff point — context surfaced, deal history ready, next action suggested. Reporting directly to the CSO, the GTM AI Specialist learns the full architecture, contributes to both layers, and progressively takes end-to-end ownership of agents in production. You are not joining a team that advises the business on AI. You are building the system that is the business. There is no playbook. You help write it.
North Star
Ship AI agents that run on real merchant data, prove their value in measurable terms, and make the sales organization faster and sharper than it would be without them. The build compounds — every signal, every call, every conversion feeds back into what you build next. You are here to make that happen.
WHAT YOU’LL DO:
- Build across both layers of the fleet — Layer 1: agents that run autonomously without rep involvement — outbound sequencing, lead prioritization, inbound triage, reactivation. Reps receive warm opportunities, not cold lists. Layer 2: agents that equip reps at the moment they step in — account context surfaced, deal history ready, next action suggested. You learn how both layers work and progressively contribute to each.
- Identify what to build and make the case for it — You are not waiting to be given a task list. You look at the sales organization, find the highest-value problem an agent could solve, and bring a structured proposal to the CSO. Judgment about what is worth building matters as much as the ability to build it.
- Test, measure, and iterate — You run experiments on real merchant data, measure whether what you built is working, identify failure modes, and refine. Every agent you touch has a documented performance trail. You do not ship and move on.
- Mine call transcripts for agent inputs — Process sales call recordings to extract patterns, category signals, and performance data. This is raw material for the agents you build — not a separate analytics workstream. You surface insights from it and design around them.
- Document and maintain what you ship — Every agent you deploy has a before/after record. You keep it current. You present it. You own what you built — not just while you're building it.
WHAT YOU BRING:
- A degree from an Ivy League or equivalent top-tier university strongly preferred— computer science, data science, economics, mathematics, or a field that taught you to think in systems. The subject matters less than the rigor of how you were trained to think.
- You have built an AI agent or automated workflow — not a class project. Something you designed, built, and iterated on because you wanted to see if it would work. You can explain what it did, what broke, and what you changed. The bar is not commercial success. The bar is that you shipped something real.
- Technical capability to build: you have used LLM APIs (OpenAI, Anthropic, or equivalent), built prompt architectures, and connected systems together. Python or equivalent. You do not need to be a software engineer — but you need to be able to build a working agent without asking someone else to write the code.
- Commercial curiosity. You read about how businesses make money. You ask why something converts and why something else doesn’t. You do not need a sales background — you need the instinct to connect what you build to a GP outcome.
- Rigor with data. You do not accept a number without understanding where it came from. You build your own measurement frameworks when none exist.
WHO YOU ARE:
- Builder first — your instinct is to build, not to ask for permission. You have side projects because you were curious, not because someone assigned them.
- AI-native, not AI-curious — you have spent real time understanding what these systems can and cannot do. You know the difference between a demo and a deployed agent.
- Comfortable with ambiguity — you can start without a complete brief, identify the next right step, and keep moving. You learn faster by doing than by waiting for clarity.
- Commercially curious — you connect what you build to a business outcome. You ask why something converts and why something doesn’t. Technology is the means; impact is the goal.
- You are early in your career. That is the point. If you don’t tick every box but you build, learn fast, and want to work on something that doesn’t yet exist — we want to hear from you.
HOW WE OPERATE:
Five principles. Non-negotiable.
- Extreme Ownership — if an agent you’re responsible for underperforms, you own the diagnosis and the fix — not the vendor, not the backlog.
- Speed Over Comfort — you ship an experiment before you’re sure it will work. You learn from live data, not from waiting.
- Impact Obsessed — every hour of your time should connect to a GP outcome — directly or as a clear step toward one.
- Simplify to Scale — you document what you build so it can be used by someone else. Complexity you create and don’t explain is debt.
- Disciplined — you keep your data clean, your experiments rigorous, and your performance logs current. Good intentions without rigour produce noise.
HOW WE MEASURE YOUR SUCCESS:
- Agent shipped: first working agent in production by day 90, with a documented hypothesis, performance data, and an honest assessment of what worked and what didn’t
- Quality of proposals: structured agent proposals to the CSO — ranked by commercial impact, grounded in data, specific about what gets built and how it gets measured
- Experiment rigour: every agent you deploy has a defined success metric set before go-live — not retrofitted afterward
- Learning progression: demonstrated improvement in AI build quality, commercial reasoning, and stack fluency quarter over quarter — assessed directly by the CSO
- Contribution to the fleet: at least one documented insight per month surfaced from call transcripts or agent performance data — standalone, with a recommendation
THE DETAILS:
- Location: Downtown Chicago (hybrid, 3 days a week in-office) + Alternate locations: Can be remote for the right fit
- Salary Range: $70,000 – $110,000 (depending on experience), plus eligibility to participate in a performance-based bonus program.
- Benefits: Medical, dental, vision, EAP, 401(k) match, ESPP, life and disability insurance, FSAs, flexible PTO, and more.
Groupon is an AI-First Company
We’re committed to building smarter, faster, and more innovative ways of working—and AI plays a key role in how we get there. We encourage candidates to leverage AI tools during the hiring process where it adds value, and we’re always keen to hear how technology improves the way you work. If you’re passionate about AI or curious to explore how it can elevate your role— you’ll be right at home here. Groupon’s purpose is to build strong communities through thriving small businesses. To learn more about the world’s largest local e-commerce marketplace, click here. You can also find out more about us in the latest Groupon news as well as learning about our DEI approach. If all of this sounds like something that’s a great fit for you, then click apply and join us on a mission to become the ultimate destination for local experiences and services.
Beware of Recruitment Fraud:
Groupon follows a merit-based recruitment process without charging job seekers any fees. We've noticed an increase in recruitment fraud, including fake job postings and fraudulent interviews and job offers aimed at stealing personal information or money. Be cautious of individuals falsely representing Groupon's Talent Acquisition team with fake job offers. If you encounter any suspicious job offers or interview calls demanding money, recognize these as scams. Groupon is not responsible for losses from such dealings. For legitimate job openings (and a sneak peek into life at Groupon), always check our official career website at Groupon Careers.
See all 258+ AI Specialist jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Specialist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as an AI Specialist
Frame your degree in a technical field
H-1B approval for AI Specialist roles hinges on specialty occupation status. A degree in computer science, statistics, mathematics, or electrical engineering maps cleanly to the role. Interdisciplinary degrees work but require stronger supporting documentation from your employer.
Target cap-exempt employers first
Universities, nonprofit research institutions, and government-affiliated labs can sponsor H-1B visas outside the annual lottery. For AI specialists, these include research labs at MIT, Stanford, and national laboratories, where demand for ML and AI talent is high year-round.
Highlight proprietary tools and model experience
USCIS scrutinizes whether AI Specialist roles genuinely require a degree. Petitions that detail work with specific frameworks like PyTorch, TensorFlow, or large language model architectures are far more defensible than generic descriptions of data analysis or automation tasks.
Don't overlook the O-1A visa pathway
If you've published research, won awards, or hold a senior position with demonstrated impact, the O-1A is worth exploring. It has no lottery, no annual cap, and AI researchers with conference publications or cited work often meet multiple qualifying criteria.
Prepare for employer RFE risk on job duty specificity
USCIS frequently issues Requests for Evidence on AI roles, questioning whether a degree is truly required. Employers should document the theoretical and applied knowledge the position demands, referencing peer-reviewed standards and internal technical specifications wherever possible.
Browse sponsoring employers before applying broadly
Not every company that posts AI roles will sponsor visas. Filtering for verified sponsoring employers on Migrate Mate before applying saves weeks of outreach to companies that will decline at the offer stage due to immigration policy constraints.
AI Specialist jobs are hiring across the US. Find yours.
Find AI Specialist JobsFrequently Asked Questions
What visa is most commonly used to sponsor AI Specialist roles in the U.S.?
The H-1B is the most common sponsorship path for AI Specialists, classifying the role as a specialty occupation requiring at least a bachelor's degree in a directly related field. USCIS approval rates for computer-related occupations, which cover most AI roles, have historically exceeded 85%. Australians also have access to the E-3 visa, which bypasses the H-1B lottery entirely.
Does my degree field matter for H-1B sponsorship as an AI Specialist?
Yes, and it matters more than most applicants expect. USCIS requires a direct relationship between your degree and the specific duties of the role. Computer science, statistics, applied mathematics, and data science degrees map cleanly. A business or humanities degree, even with extensive AI experience, makes the petition significantly harder to approve without supplemental evidence of equivalent education.
How competitive is the H-1B lottery for AI Specialist roles?
The lottery is the same for all cap-subject H-1B petitions regardless of job title, with a selection rate around 25% in recent years. However, AI Specialists hired by universities, nonprofit research organizations, or government-affiliated entities are cap-exempt and bypass the lottery entirely. Many AI professionals pursue these roles specifically to avoid lottery dependency.
Can I get sponsored as an AI Specialist without a traditional four-year degree?
It's possible but more complex. USCIS allows three years of specialized work experience to substitute for one year of formal education, meaning 12 years of directly relevant experience can satisfy a four-year degree requirement. In practice, this standard is difficult to meet for AI roles without documented, progressive technical responsibility. An immigration attorney should evaluate your specific profile before an employer files.
Where can I find AI Specialist jobs that are open to visa sponsorship?
Migrate Mate is built specifically for this, listing AI Specialist roles from employers who have actively sponsored work visas. Filtering by sponsorship status upfront means you're only seeing companies with a verified track record of filing H-1B or other work visa petitions, rather than discovering late in the process that a company doesn't sponsor international candidates.
What is the prevailing wage requirement for sponsored AI Specialist 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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