Full-Stack Product Engineer (React/Next.JS + AI Infrastructu

• Strong professional experience with React, Next.js, TypeScript and modern JavaScript.
• Experience building and debugging production web applications and customer-facing user flows.
• Ability to investigate difficult issues across frontend code, APIs, backend services, browser behavior and third-party integrations.
• Node.js experience and an understanding of REST APIs, databases, authentication and server-side application behavior.
• Experience writing automated tests, preferably with Playwright or another end-to-end browser-testing framework.
• Experience with product analytics, session replay, error tracking or production-monitoring tools.
• Practical Linux, Docker, Git and CI/CD experience.
• Experience working with e-commerce applications, carts, checkout flows, payments or related integrations.
• Regular, effective use of AI development tools such as Codex, Claude Code, Cursor or similar systems.
• Ability to understand, test and verify AI-generated work rather than accepting it without review.
• Strong problem-solving, written communication and documentation skills.
• Able to work independently while communicating clearly with a small founder-led team.
• Fluent professional English.
• Available approximately 40 hours per week with at least four daily hours overlapping Eastern Time.
• Comfortable beginning with a paid technical trial before transitioning into a long-term role.

• Diagnose and fix production React, Next.js and TypeScript bugs affecting storefront reliability and conversion.
• Investigate cart, checkout, promotion, mobile and browser-session failures.
• Improve PostHog event tracking, funnels, session replay, error monitoring and alerts.
• Build Playwright end-to-end tests for critical customer journeys and configure BrowserStack coverage.
• Develop and maintain frontend features, backend services and third-party integrations.
• Help manage Linux servers, Docker environments, CI/CD pipelines, networking and cloud infrastructure.
• Support GPU machines, locally hosted AI models and internal AI coding-agent workflows.
• Use AI development tools effectively while reviewing, testing and understanding all resulting code.
• Document root causes, technical decisions and regression coverage.
• Work directly with the founders to prioritize and deliver improvements.

Success will be measured by fewer production regressions, faster issue resolution, stronger automated test coverage, more reliable analytics and demonstrable improvements to customer experience and conversion.