Full Stack Product Intern

Job description

## About the role Hibiscustech is building an AI‑powered online gaming playground under the PsyPlay brand. The company is reimagining classic games such as Chess, Ludo, Connect 4, and Poker with smart features, deep analytics, and a multiplayer experience. As a **Full Stack Product Intern** you will join the early‑team, working on a product that will shape the future of AI‑driven consumer gaming. ## What you'll learn and build **Frontend Learning (React / React Native + Gameplay UI)** - Build modern interactive UIs with **Next.js** - Create clean, reusable components for game screens, dashboards, and profiles - Integrate real‑time features like gameplay, replays, and leaderboards - Work with basic Canvas/SVG animations for a delightful UX **Backend Learning (APIs + Game Platform Core)** - Develop backend services in **Go** or **Python** - Design APIs for matchmaking, player stats, and game history - Work with **PostgreSQL** (schema design and queries) - Connect authentication systems using **Firebase** - Gain exposure to scalable backend architecture step‑by‑step ## Required qualifications - Basic programming confidence (React, React Native, Python, C++ or similar) - Strong interest in full‑stack development and willingness to learn both frontend and backend stacks - Comfortable using **Git** and debugging code - Builder mindset with a focus on clean code and thoughtful design **Nice‑to‑have** - Personal React projects or portfolio - Any prior exposure to backend/API development - Passion for games, chess, or competitive systems - Curiosity about AI technologies ## Benefits - Real ownership: your work directly impacts the product and its players - Mentorship from founders and senior engineers - Opportunity to earn credibility for a future core or co‑founder role - Flexible hours and a fully remote‑friendly environment - Possibility of a paid or equity‑based role as the company grows

Required skills

Compensation

Salary for this role is not disclosed by the employer. We don’t have enough benchmark data from similar roles to produce a reliable estimate. The actual compensation will be discussed during the interview process.