OPT AI Product Engineer Jobs
AI Product Engineer roles sit at the intersection of machine learning and product development, making them a strong fit for F-1 OPT students with STEM degrees in computer science, data science, or AI. Most roles qualify for the 24-month STEM OPT extension, giving you up to three years of authorized work experience.
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Get Access To All JobsINTRODUCTION
We're looking for an AI Product Engineer to build and ship enterprise tools, systems and automations that drive measurable operational savings or improvements across Rivian's Facilities organization. You'll use AI-native development tools like Cursor, Gemini, and Claude to turn real Facilities problems into working solutions that save time, reduce cost, and eliminate manual overhead. You'll embed directly into Facilities workflows — construction project reporting, capital program tracking, real estate operations, building management — and build automations that have a tangible dollar-and-cents impact.
ROLE AND RESPONSIBILITIES
Build & Deploy
- Build internal applications, AI agents, and workflow automations using LLM-assisted development tools (Cursor, Gemini, Claude, Glean, etc.) targeting specific Facilities pain points — manual reporting, data entry, schedule tracking, cost reconciliation — with a focus on quantifiable time and cost savings
- Stand up no-code and low-code solutions, maintainable by non-technical team members where speed and simplicity are prioritized over engineering complexity
- Connect Facilities data sources (ACC, Procore, Kahua, FOS, Databricks) via APIs to support intelligent workflows that unify siloed information
- Own the Full SDLC by applying traditional product development rigor to AI-generated code. You will manage sprint cycles, define technical requirements in Jira, and oversee the end-to-end lifecycle of the tools you build.
- Conduct code reviews on peer-built AI tools and own enhancement of deployed solutions based on user feedback and evolving business needs
Learn the Business
- Rapidly build working knowledge of Facilities operations — how capital projects are planned, budgeted, tracked, and delivered — by shadowing project managers, construction teams, and operations staff to find automation opportunities that aren't on anyone's roadmap yet
- Understand the Facilities tech stack well enough to identify where AI can eliminate friction and reduce costs
- Document solutions, create reusable templates, and contribute to internal playbooks and how-to guides
Collaborate & Deliver Value
- Partner with Facilities stakeholders to understand workflows, quantify inefficiencies, and prioritize automations with the highest operational ROI
- Translate operational needs into working prototypes and iterate based on user feedback until adoption sticks
- Help track and report the impact of deployed solutions — hours saved, errors reduced, costs avoided, scaling without new headcount
BASIC QUALIFICATIONS
- 4+ years in a technical role — software development, product ownership, technical program management, or similar
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field; OR equivalent practical, hands-on experience in lieu of a degree
- Demonstrated experience building with AI-assisted coding tools (Cursor, Codex, Claude Code, or equivalent)
- Working knowledge of prompt engineering, AI agent design, and LLM application development
- Strong foundational knowledge of Agile methodologies, version control (Git), code reviews, and secure deployment pipelines
- Strong UI/UX instincts — can produce functional, clean interfaces without a design team
- Strong communication skills; equally comfortable in a whiteboard session with leadership or a working session with project teams
- Self-directed; thrives in ambiguous environments where the playbook doesn’t exist yet
PREFERRED QUALIFICATIONS
- Familiarity with large-scale construction, real estate, or capital programs
- Experience with enterprise AI tools like Glean or similar knowledge management platforms
- Exposure to MCP (Model Context Protocol) frameworks and multi-agent architectures
- Prior experience shipping internal tools in a non-engineering business unit
- Track record of upskilling peers or running internal training on new technologies
LI-Hybrid
INTRODUCTION
We're looking for an AI Product Engineer to build and ship enterprise tools, systems and automations that drive measurable operational savings or improvements across Rivian's Facilities organization. You'll use AI-native development tools like Cursor, Gemini, and Claude to turn real Facilities problems into working solutions that save time, reduce cost, and eliminate manual overhead. You'll embed directly into Facilities workflows — construction project reporting, capital program tracking, real estate operations, building management — and build automations that have a tangible dollar-and-cents impact.
ROLE AND RESPONSIBILITIES
Build & Deploy
- Build internal applications, AI agents, and workflow automations using LLM-assisted development tools (Cursor, Gemini, Claude, Glean, etc.) targeting specific Facilities pain points — manual reporting, data entry, schedule tracking, cost reconciliation — with a focus on quantifiable time and cost savings
- Stand up no-code and low-code solutions, maintainable by non-technical team members where speed and simplicity are prioritized over engineering complexity
- Connect Facilities data sources (ACC, Procore, Kahua, FOS, Databricks) via APIs to support intelligent workflows that unify siloed information
- Own the Full SDLC by applying traditional product development rigor to AI-generated code. You will manage sprint cycles, define technical requirements in Jira, and oversee the end-to-end lifecycle of the tools you build.
- Conduct code reviews on peer-built AI tools and own enhancement of deployed solutions based on user feedback and evolving business needs
Learn the Business
- Rapidly build working knowledge of Facilities operations — how capital projects are planned, budgeted, tracked, and delivered — by shadowing project managers, construction teams, and operations staff to find automation opportunities that aren't on anyone's roadmap yet
- Understand the Facilities tech stack well enough to identify where AI can eliminate friction and reduce costs
- Document solutions, create reusable templates, and contribute to internal playbooks and how-to guides
Collaborate & Deliver Value
- Partner with Facilities stakeholders to understand workflows, quantify inefficiencies, and prioritize automations with the highest operational ROI
- Translate operational needs into working prototypes and iterate based on user feedback until adoption sticks
- Help track and report the impact of deployed solutions — hours saved, errors reduced, costs avoided, scaling without new headcount
BASIC QUALIFICATIONS
- 4+ years in a technical role — software development, product ownership, technical program management, or similar
- Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field; OR equivalent practical, hands-on experience in lieu of a degree
- Demonstrated experience building with AI-assisted coding tools (Cursor, Codex, Claude Code, or equivalent)
- Working knowledge of prompt engineering, AI agent design, and LLM application development
- Strong foundational knowledge of Agile methodologies, version control (Git), code reviews, and secure deployment pipelines
- Strong UI/UX instincts — can produce functional, clean interfaces without a design team
- Strong communication skills; equally comfortable in a whiteboard session with leadership or a working session with project teams
- Self-directed; thrives in ambiguous environments where the playbook doesn’t exist yet
PREFERRED QUALIFICATIONS
- Familiarity with large-scale construction, real estate, or capital programs
- Experience with enterprise AI tools like Glean or similar knowledge management platforms
- Exposure to MCP (Model Context Protocol) frameworks and multi-agent architectures
- Prior experience shipping internal tools in a non-engineering business unit
- Track record of upskilling peers or running internal training on new technologies
LI-Hybrid
See all 511+ OPT AI Product Engineer Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as an AI Product Engineer
Lead with your STEM OPT eligibility
AI Product Engineer roles almost universally qualify for the 24-month STEM OPT extension. Mentioning your eligibility upfront removes the employer's biggest concern and signals you've done the homework on your own authorization status.
Target companies with active H-1B sponsorship history
Companies that have sponsored H-1B visas before are significantly more likely to support OPT employees through the transition. Focus your applications on employers with a documented pattern of sponsoring technical roles in machine learning or product engineering.
Position your AI skills around business outcomes
Hiring managers for product-facing AI roles care about shipped features and measurable impact, not just model accuracy. Frame your experience around what you built, who used it, and what improved. This shifts the conversation from authorization to value.
Apply early in your OPT window
Many employers hesitate when OPT expiration is close. Applying within the first six months of your initial OPT period gives companies confidence they'll have time to evaluate you and begin H-1B planning well before your authorization runs out.
Build a portfolio of deployed AI work
Demonstrated product thinking sets AI Product Engineers apart from pure researchers. Showcase projects where you integrated a model into a real application, handled edge cases, and iterated based on user feedback. GitHub and personal projects both count.
Be direct about your timeline in interviews
Proactively explaining your OPT timeline, STEM extension eligibility, and H-1B lottery calendar builds trust rather than creating uncertainty. Employers appreciate candidates who understand the process and can plan around it without requiring hand-holding.
AI Product Engineer OPT: Frequently Asked Questions
Do AI Product Engineer jobs qualify for the 24-month STEM OPT extension?
Most do, provided your degree is in a STEM-designated field such as computer science, electrical engineering, data science, or a related discipline. The role itself must also be directly related to your field of study. AI Product Engineer positions typically satisfy this requirement given their foundation in applied machine learning and software systems, but your DSO must confirm eligibility based on your specific degree and CIP code.
How do I find AI Product Engineer employers who are open to OPT candidates?
Migrate Mate is built specifically for F-1 OPT students and surfaces AI Product Engineer roles at companies that have demonstrated willingness to sponsor or support international candidates. Filtering by OPT-friendly employers saves time compared to applying broadly and hitting walls mid-process. Prioritize companies with an existing H-1B sponsorship track record in technical roles, since that signals a clear pathway beyond your initial authorization period.
What happens to my OPT if I'm laid off from an AI Product Engineer role?
You have a 60-day grace period from the date your employment ends to find a new OPT-authorized position, transfer to a different visa status, or depart the U.S. During this window, you cannot work. If you secure a new role within 60 days, your DSO updates your SEVIS record with the new employer. Staying unemployed beyond 60 days puts you out of status, so it's critical to act quickly.
Can I work as a contractor or freelancer as an AI Product Engineer on OPT?
Yes, OPT permits self-employment and independent contracting as long as the work is directly related to your degree field and you can document it properly. For an AI Product Engineer, this typically means contract projects involving model development, AI integration, or product feature work. You must log hours in your SEVIS record and ensure each engagement is clearly tied to your field of study to remain compliant.
Does having a master's degree versus a bachelor's degree affect my OPT options for this role?
Your OPT period is the same regardless of degree level: 12 months of initial OPT plus a potential 24-month STEM extension if you qualify. However, a master's degree in a STEM field does improve your H-1B lottery odds, since master's graduates from U.S. institutions are entered into both the regular cap and the advanced degree exemption pool. For AI Product Engineer roles specifically, a master's also tends to open doors to more senior product and research-adjacent positions.