AI Product Engineer (Full Stack)
Job Title: AI Product Engineer (Full Stack)
Position Type: Full-Time, Remote
Working Hours: U.S. Business Hours
About the Role
We’re hiring an execution-focused AI Product Engineer (Full Stack) to build and scale a production-ready web application from the ground up.
This is a hands-on role for someone who can take full ownership of both frontend and backend development while integrating AI capabilities into real-world product use cases.
This is not a support or maintenance role — it requires building, shipping, and iterating on a live product with strong system design, performance, and reliability.
What You’ll Own
Full Product Development (End-to-End)
- Build and launch a production-ready web application from concept to deployment.
- Own both frontend and backend development across the full stack.
- Continuously iterate and improve the product post-launch.
AI Integration & Workflows
- Design and implement AI-driven workflows within the product.
- Integrate LLMs (e.g., Claude or similar) into real use cases.
- Implement guardrails to manage AI limitations (hallucinations, edge cases).
Backend Systems & Infrastructure
- Build and manage backend systems using Supabase or similar tools.
- Design scalable APIs and data structures.
- Ensure efficient data handling and system performance.
Security & System Reliability
- Implement authentication, permissions, and data protection practices.
- Ensure system security and integrity across the platform.
- Optimize performance, scalability, and reliability.
Product Collaboration & Iteration
- Work closely with leadership to rapidly ship and improve features.
- Translate product ideas into working technical solutions.
- Continuously refine the system based on feedback and usage.
Debugging & Optimization
- Identify and fix system issues and bugs.
- Improve system stability and user experience.
- Maintain high-quality code and system performance.
Must-Have Experience & Skills
Non-Negotiables
- Strong full stack development experience (frontend + backend).
- Proven track record of building and shipping real, production-level products.
- Hands-on experience integrating AI/LLMs into applications.
- Strong understanding of system architecture and API design.
- Experience with Supabase or similar backend platforms.
- Strong understanding of AI limitations (hallucinations, failure handling).
- Knowledge of security best practices (authentication, permissions, data protection).
- Ability to work independently and take full ownership of product development.
Nice-to-Haves
- Experience building AI agents or automation workflows.
- Familiarity with Claude or similar LLM tools in production.
- Experience building SaaS or operational platforms.
- Exposure to aviation, logistics, or membership systems.
- Experience scaling products from MVP to production.
Key Metrics for Success
- Successful launch of production-ready application.
- Stability and performance of the system.
- Quality and effectiveness of AI integrations.
- Speed of feature delivery and iteration.
- Reduction in bugs and system issues over time.
- Scalability and maintainability of the platform.
Interview Process
- Initial Screening Call
- Technical & Systems Design Interview
- Practical Task (Product Build / AI Integration Scenario)
- Final Interview
- Internal Review & Approval
- Offer & Onboarding
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