AI Product Owner Jobs for OPT Students
AI Product Owner jobs are well-suited for F-1 OPT students with backgrounds in computer science, data science, or engineering management. Most roles require a technical degree, which aligns cleanly with OPT eligibility. Your 12-month OPT window is enough to complete a full product cycle, and STEM OPT extension applies if your degree qualifies.
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Get Access To All JobsJob Title: AI Product Manager
Location: New York, New York
Firm Overview:
Cantor Fitzgerald, with over 16,000 employees, has been a leading global financial services firm at the forefront of financial and technological innovation since 1945. Cantor is a preeminent investment bank serving more than 5,000 institutional clients around the world, recognized for its strengths in fixed income and equity capital markets, investment banking, SPAC underwriting, PIPE placements, commercial real estate, and for its global distribution platform. Capitalizing on the firm’s financial acumen and technology prowess, Cantor’s portfolio of businesses also includes Prime Brokerage, Asset Management, and other businesses and ventures. Cantor has consistently fueled the growth of original ideas, pioneered new markets, and provided superior service to clients. Cantor operates trading desks in every major financial center globally, with offices in over 30 locations around the world. As one of the few remaining private partnerships on Wall Street, Cantor has the distinct ability to focus on long-term value creation and solid relationship building. Our structure allows us to respond quickly to client needs, develop solutions that address complex challenges, avoid the limitations of bureaucracy, and attract talented individuals who are driven to succeed.
Responsibilities:
Cantor's equities business is standing up a dedicated AI function, and this is one of its first hires. The AVP/VP will own workstreams across AI product development and user enablement — designing solutions, building prototypes, driving adoption, and managing stakeholder relationships across the business. You will work directly with traders, research analysts, salespeople, operations, compliance, legal, and technology teams to turn real business problems into working AI tools that people use. This is a hands-on builder role with real ownership, not a support function. You will carry initiatives from problem identification through delivery and adoption, often managing multiple workstreams simultaneously. The right person operates with a founder's mindset inside a large organization — defining what needs to happen next, not waiting to be told.
- Own the design, build, and iteration of AI-powered solutions — from initial architecture through production deployment and ongoing improvement.
- Build working prototypes end-to-end: data integration, application logic, and user-facing interfaces. This is a hands-on builder role.
- Partner with front-office teams (research, sales, trading), operations, compliance, legal, and technology to translate business problems into shippable AI products.
- Own solution quality — track usage, performance, and outcomes of deployed tools; iterate based on evidence, not assumptions.
Program & Enablement
- Design and run the enablement infrastructure that drives real adoption: training programs, documentation, user support channels, and feedback loops.
- Manage the demand pipeline for AI requests within assigned business areas — intake, prioritize, scope, and communicate transparently.
- Measure what matters: adoption rates, proficiency gains, support volume trends, and business outcomes. Use data to iterate the program, not just report on it.
Qualifications
- 3+ years in product, technology, data, or analytics roles with increasing ownership. Bachelor's degree required; CS, engineering, or data science preferred.
- Builder, not just a spec writer. Full-stack prototyping capability (data → logic → interface). Working knowledge of systems architecture, APIs, data flows, and SDLC practices. Engineers should find you credible.
- AI depth beyond tutorials. You architect LLM systems — context engineering, evaluation, guardrails, cost/quality tradeoffs — not just call APIs. You can design agent workflows, know when simpler approaches win, and have a rigorous method for defining and measuring "good" output. You stay at the frontier and experiment with new models and tools on your own initiative.
- Ownership pattern. Your best stories start with "I noticed..." not "I was asked to." When blocked, you find another path. Sustained delivery across workstreams, not a single heroic sprint.
- Full-lifecycle product thinking. Problem identification → requirements → build → launch → enablement → adoption → iteration, treated as one integrated system. Experience standing up enablement programs and getting people who don't report to you to change behavior.
- Enterprise constraint navigation. Comfortable designing AI solutions within compliance, data sensitivity, and regulatory requirements. Financial services experience preferred; sell-side equities familiarity is a plus.
Educational Qualifications:
Bachelor’s Degree required
Salary:
$115,000 - $155,000
The actual base salary will be determined on an individualized basis considering a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package (including health, vision, and dental insurance, paid time off and a 401(k) retirement), this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.).
We do not accept unsolicited resumes, candidate referrals, or outreach from third-party recruiters or staffing agencies. Any such submissions will be considered property of Cantor Fitzgerald and will not be eligible for any placement fee. Recruiters must have a signed agreement with our Talent Acquisition team and be invited to submit candidates for a specific role. Direct contact with hiring managers or employees is strictly prohibited.
Job Title: AI Product Manager
Location: New York, New York
Firm Overview:
Cantor Fitzgerald, with over 16,000 employees, has been a leading global financial services firm at the forefront of financial and technological innovation since 1945. Cantor is a preeminent investment bank serving more than 5,000 institutional clients around the world, recognized for its strengths in fixed income and equity capital markets, investment banking, SPAC underwriting, PIPE placements, commercial real estate, and for its global distribution platform. Capitalizing on the firm’s financial acumen and technology prowess, Cantor’s portfolio of businesses also includes Prime Brokerage, Asset Management, and other businesses and ventures. Cantor has consistently fueled the growth of original ideas, pioneered new markets, and provided superior service to clients. Cantor operates trading desks in every major financial center globally, with offices in over 30 locations around the world. As one of the few remaining private partnerships on Wall Street, Cantor has the distinct ability to focus on long-term value creation and solid relationship building. Our structure allows us to respond quickly to client needs, develop solutions that address complex challenges, avoid the limitations of bureaucracy, and attract talented individuals who are driven to succeed.
Responsibilities:
Cantor's equities business is standing up a dedicated AI function, and this is one of its first hires. The AVP/VP will own workstreams across AI product development and user enablement — designing solutions, building prototypes, driving adoption, and managing stakeholder relationships across the business. You will work directly with traders, research analysts, salespeople, operations, compliance, legal, and technology teams to turn real business problems into working AI tools that people use. This is a hands-on builder role with real ownership, not a support function. You will carry initiatives from problem identification through delivery and adoption, often managing multiple workstreams simultaneously. The right person operates with a founder's mindset inside a large organization — defining what needs to happen next, not waiting to be told.
- Own the design, build, and iteration of AI-powered solutions — from initial architecture through production deployment and ongoing improvement.
- Build working prototypes end-to-end: data integration, application logic, and user-facing interfaces. This is a hands-on builder role.
- Partner with front-office teams (research, sales, trading), operations, compliance, legal, and technology to translate business problems into shippable AI products.
- Own solution quality — track usage, performance, and outcomes of deployed tools; iterate based on evidence, not assumptions.
Program & Enablement
- Design and run the enablement infrastructure that drives real adoption: training programs, documentation, user support channels, and feedback loops.
- Manage the demand pipeline for AI requests within assigned business areas — intake, prioritize, scope, and communicate transparently.
- Measure what matters: adoption rates, proficiency gains, support volume trends, and business outcomes. Use data to iterate the program, not just report on it.
Qualifications
- 3+ years in product, technology, data, or analytics roles with increasing ownership. Bachelor's degree required; CS, engineering, or data science preferred.
- Builder, not just a spec writer. Full-stack prototyping capability (data → logic → interface). Working knowledge of systems architecture, APIs, data flows, and SDLC practices. Engineers should find you credible.
- AI depth beyond tutorials. You architect LLM systems — context engineering, evaluation, guardrails, cost/quality tradeoffs — not just call APIs. You can design agent workflows, know when simpler approaches win, and have a rigorous method for defining and measuring "good" output. You stay at the frontier and experiment with new models and tools on your own initiative.
- Ownership pattern. Your best stories start with "I noticed..." not "I was asked to." When blocked, you find another path. Sustained delivery across workstreams, not a single heroic sprint.
- Full-lifecycle product thinking. Problem identification → requirements → build → launch → enablement → adoption → iteration, treated as one integrated system. Experience standing up enablement programs and getting people who don't report to you to change behavior.
- Enterprise constraint navigation. Comfortable designing AI solutions within compliance, data sensitivity, and regulatory requirements. Financial services experience preferred; sell-side equities familiarity is a plus.
Educational Qualifications:
Bachelor’s Degree required
Salary:
$115,000 - $155,000
The actual base salary will be determined on an individualized basis considering a wide range of factors including, but not limited to, relevant skills, experience, education, and, where applicable, licenses or certifications held. In addition to base salary and a competitive benefits package (including health, vision, and dental insurance, paid time off and a 401(k) retirement), this position may be eligible for additional types of compensation including discretionary bonuses and other short- and long-term incentives (e.g., deferred cash, equity, etc.).
We do not accept unsolicited resumes, candidate referrals, or outreach from third-party recruiters or staffing agencies. Any such submissions will be considered property of Cantor Fitzgerald and will not be eligible for any placement fee. Recruiters must have a signed agreement with our Talent Acquisition team and be invited to submit candidates for a specific role. Direct contact with hiring managers or employees is strictly prohibited.
How to Get Visa Sponsorship as an AI Product Owner
Lead with technical depth, not just product instincts
AI Product Owners who can read model documentation, interpret evaluation metrics, and speak credibly with ML engineers get further in interviews. Employers sponsoring OPT students want candidates who reduce friction, not add it.
Target companies actively building AI products
Companies mid-build on AI products are more likely to sponsor because they need product talent urgently. Search Migrate Mate to find employers with active OPT sponsorship history in product and AI roles specifically.
Document your STEM OPT eligibility early
If your degree is in computer science, information systems, or a related STEM field, confirm your eligibility for the 24-month extension before you start applying. Employers weighing sponsorship costs want to know your authorized period upfront.
Frame your thesis or capstone as product experience
If you led a technical project with defined requirements, stakeholders, and outcomes, that maps directly to AI product ownership. Reframe academic work in product language: user stories, success metrics, and iteration cycles.
Get specific about which AI systems you have experience with
Vague claims about AI exposure will not move hiring managers. Name the models, frameworks, or platforms you worked with and describe the product context. Specificity signals real experience rather than resume padding.
Ask about H-1B sponsorship intent in the second interview, not the first
Raising visa sponsorship too early signals risk to some hiring managers. Once you have demonstrated fit and the conversation has moved past initial screening, ask directly whether the company sponsors H-1B for strong performers.
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Get Access To All JobsFrequently Asked Questions
Do AI Product Owner roles qualify for the STEM OPT extension?
It depends on your degree, not the job title. If you graduated with a STEM-designated degree such as computer science, data science, or engineering management, you can apply for the 24-month STEM OPT extension regardless of your job title. The role itself does not need to be classified as STEM. Confirm your program's CIP code with your DSO before applying.
How early should I start applying for AI Product Owner jobs on OPT?
Start at least three months before your OPT start date. AI product roles often involve multi-stage interviews including take-home case studies and technical reviews, which can take four to six weeks to complete. Applying early also gives employers time to verify your authorization status and align on your start date without feeling rushed.
What degree backgrounds do employers typically accept for AI Product Owner roles on OPT?
Computer science, information systems, data science, and engineering management are the most common degree backgrounds for this role. Some employers also accept economics or business degrees if the candidate has a strong technical portfolio. Since OPT ties your work authorization to your field of study, a technical degree will both strengthen your application and support STEM extension eligibility.
Where can I find AI Product Owner jobs that are open to OPT candidates?
Migrate Mate is built specifically for F-1 OPT students and filters job listings by visa sponsorship status, so you are not wasting applications on employers who do not sponsor. You can browse AI Product Owner roles with verified sponsorship history, which is especially useful when your OPT clock is running and you need to be strategic about where you apply.
Can I work as an AI Product Owner at a startup on OPT?
Yes. OPT work authorization is not limited to large employers. Startups can sponsor OPT students as long as the employment is paid, directly related to your field of study, and the employer follows standard authorization requirements. Smaller companies may move faster through the interview process, which can be an advantage when you have a limited OPT window remaining.
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