Job Description

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