Full-Stack Developer (AI-First Product) 1781

This is a remote position.

Full-Stack Developer (AI-First Product) Schedule: Full-time, remote 8:00 AM – 5:00 PM EST Flexible schedule with at least 50% overlap with EST (U.S. Eastern Time) Availability to attend meetings and respond to key communications outside strict working hours when required Job description: We are seeking a highly proactive and AI-driven Full-Stack Developer to join an early-stage product team building a modern software platform for the waste hauling and logistics industry. This is a zero-to-one opportunity, where the selected candidate will directly influence product direction, architecture, and scalability. You will work closely with leadership and a technical stakeholder, contributing across the entire lifecycle—from product discovery and architecture design to deployment and optimization. This role requires a builder mindset, not just execution, with strong ownership and the ability to challenge ideas, identify risks, and propose better solutions. The ideal candidate is passionate about coding, experienced in modern development practices, and comfortable working in an AI-first environment, leveraging tools like Cursor, Claude, or similar while maintaining strong core engineering fundamentals. Responsibilities: Architect and build a scalable, modular web application from scratch using modern frameworks (e.g., Next.js, TypeScript) Design and implement REST APIs and webhook systems for integration with third-party tools (CRM, billing, logistics systems, etc.) Develop AI-powered features to improve workflows, automation, and user experience Collaborate in product discovery and help identify edge cases, technical gaps, and optimization opportunities Contribute to market and workflow understanding to support product development decisions Own the full development lifecycle, including deployment, testing, monitoring, and CI/CD Build a flexible and extensible system that can support future integrations and product expansion Participate in pair programming sessions (~10%) to review work, share knowledge, and align with stakeholders Evaluate and recommend technologies, tools, and architectures based on best fit, not familiarity