• Build the future of online shopping as a Full Stack Developer (m/f/d) • Play a central role in developing our AI-powered services for retail • Develop high-performance backend systems, smart frontends and innovative AI features using state-of-the-art technology • Develop and maintain scalable REST APIs with NestJS • Build AI-powered services for product search, GPT-based communication, TTS output and tool calls • Integrate LLM APIs into production systems • Efficient data modeling with MongoDB, including aggregations and performance optimization • Deploy and operate in Azure using Docker, including monitoring and error handling • Implement parallel tool calls and event streaming via SSE or WebSockets • Connect external APIs (CMS, e-commerce platforms such as Shopify/WooCommerce, Google Feeds, etc.)

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 #LI-AG1

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 #LI-AG1

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 #LI-AG1