STEM OPT AI Product Engineer Jobs
AI Product Engineer roles sit squarely in STEM-designated fields, making them strong candidates for the 24-month STEM OPT extension beyond your initial 12 months. Your employer must be enrolled in E-Verify, and your degree in computer science, engineering, or a related STEM discipline must align with the role's CIP code to qualify.
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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 410+ STEM OPT AI Product Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT AI Product Engineer Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as an AI Product Engineer
Verify your CIP code before applying
Your STEM degree's CIP code must align with the AI Product Engineer role to qualify for the 24-month extension. Cross-reference your program against the DHS STEM Designated Degree Program List before submitting any application to avoid surprises at the extension stage.
Confirm E-Verify enrollment before accepting offers
Ask your recruiter to confirm their E-Verify company ID number before you sign anything. An employer who isn't enrolled cannot legally employ you on STEM OPT, and onboarding won't fix that gap retroactively.
Use O*NET to frame your technical experience
AI Product Engineer roles map to specific SOC codes in O*NET. Pull the listed tasks and knowledge areas from your occupation profile and mirror that language in your resume and I-983 training plan to strengthen the practical training connection.
File your I-983 training plan before day one
Your I-983 must be signed by both you and your employer and submitted to your DSO before your STEM OPT extension start date. A gap in your training plan documentation can jeopardize your work authorization, not just your extension approval.
Target companies with active LCA filings in AI roles
Employers who have filed Labor Condition Applications for AI or machine learning engineers have already cleared the DOL wage certification process. Use Migrate Mate to filter for companies with verified LCA filing history in this space, so you're targeting roles where sponsorship infrastructure already exists.
Check prevailing wage tiers before negotiating
Look up the wage level for AI Product Engineer roles in your target metro using the OFLC Wage Search before any offer conversation. Employers filing an LCA must pay at least the prevailing wage, so knowing the floor helps you negotiate from an informed position.
Frequently Asked Questions
Does an AI Product Engineer role qualify for the STEM OPT extension?
It depends on two things: your degree's CIP code and the role's SOC code. AI Product Engineer positions typically map to computer science or engineering SOC codes that appear on the DHS STEM Designated Degree Program List. Your DSO confirms eligibility at the extension stage, so align your CIP code with the role before applying rather than after you've accepted an offer.
What E-Verify requirement applies to my STEM OPT employer?
Every employer who hires you on a STEM OPT extension must be enrolled in E-Verify at the specific worksite where you'll work. A company-wide enrollment doesn't automatically cover a subsidiary, a remote office, or a staffing arrangement. Ask your recruiter for the E-Verify company ID and verify enrollment status through the E-Verify employer search before your start date.
What should my I-983 training plan include for an AI Product Engineer role?
Your I-983 must describe concrete learning objectives tied to your STEM degree, not just your job duties. For an AI Product Engineer, that means documenting how the role builds skills in machine learning systems, product development methodologies, or data engineering, connecting each objective back to your academic training. Both you and your employer sign it, and your DSO must receive it before your extension begins.
How does cap-gap protection work if my H-1B is selected while I'm on STEM OPT?
If your H-1B visa petition is filed before your STEM OPT expires and USCIS selects it in the lottery, cap-gap automatically extends your OPT work authorization through September 30 of that fiscal year. You can continue working as an AI Product Engineer without interruption, provided your employer remains E-Verify enrolled and your I-983 stays current through the cap-gap period.
Where can I find AI Product Engineer jobs where employers are already set up for STEM OPT?
Migrate Mate filters AI Product Engineer listings by employers with verified E-Verify enrollment and LCA filing history, so you're not spending weeks vetting companies that can't support your work authorization. Searching there surfaces roles where the employer has already navigated the DOL filing process for similar positions, which significantly shortens the path from offer to compliant employment.