Job 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)
• Final Interview
• Internal Review & Approval
• Offer & Onboarding

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