Job Description - AI Product Engineer (Full Stack)
Description
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)
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