We are looking for a curious, fast-learning Full Stack Developer Intern who is excited to build software in an AI-native way. You will develop real-world web applications with React.js on the frontend and Node.js on the backend — but the way you build matters as much as what you build. You'll pair with AI coding assistants such as Claude / Claude Code and GitHub Copilot / OpenAI Codex as everyday tools to build and ship real-world features faster.
This is a hands-on role for someone who wants to move beyond "just coding" and understand how modern teams prototype an MVP in days, embed AI into the SDLC, and ship production-grade features faster and with more confidence.
What Makes This Role Different
- AI-first workflow: you'll use AI assistants for scaffolding, refactoring, test generation, code review, and documentation — while learning when to trust them and when not to.
- MVP mindset: rapidly turn ideas into working prototypes, validate them, and iterate — using AI to compress the build cycle.
- Real ownership: your work ships to production-grade applications, not throwaway sandboxes.
Key Responsibilities
- Develop responsive, interactive user interfaces using React.js (Hooks, component patterns, state management).
- Build and maintain RESTful APIs using Node.js and Express.js, and integrate frontend with backend services.
- Work with databases such as MongoDB or MySQL, including basic schema and query design.
- Use AI coding assistants (Claude Code, Codex/Copilot, Cursor) to scaffold features, write and refactor code, generate tests, and speed up debugging — reviewing every suggestion critically.
- Rapidly build MVPs and prototypes, then iterate based on feedback and metrics.
- Write clean, maintainable, well-documented code; participate in code reviews and team discussions.
Required Skills
- Good understanding of JavaScript (ES6+).
- Basic knowledge of React.js (components, props, state, Hooks).
- Basic understanding of Node.js and Express.js.
- Familiarity with responsive web design.
- Understanding of REST APIs and JSON.
- Basic knowledge of Git and GitHub.
- Familiarity with databases like MongoDB or MySQL.
- Hands-on exposure to at least one AI coding assistant — Claude / Claude Code, GitHub Copilot, OpenAI Codex, Cursor, or similar — and genuine curiosity about using them well.
- Strong problem-solving and analytical skills; good communication and a strong willingness to learn.
Preferred / Bonus Skills
- Fluency with AI coding assistants — using Claude Code, Copilot, Codex, or Cursor to work faster on real projects.
- Knowledge of TypeScript; state tools like Redux, Context API, or React Hooks.
- Exposure to cloud platforms (AWS, Azure, or GCP).
- Understanding of authentication using JWT or OAuth; API testing with Postman.
Eligibility
- Open to recent graduates and self-taught developers.
- Candidates who have completed relevant projects, internships, or certifications — especially any that used AI tools — are strongly encouraged to apply.
- A GitHub profile, portfolio, or a short demo of something you built (bonus points if AI was part of it).
Initial Screening — What to Submit
Instead of a traditional résumé screen, we ask every applicant to show us something you built. Two things are required:
- A working prototype — a small but functional app or feature (web app, tool, or MVP). It doesn't need to be polished or large; it needs to actually run. Share a live link and/or a public repository.
- A short build write-up — documentation of how you built it using AI agents / assistants (Claude Code, Copilot, Codex, Cursor, etc.). Walk us through what you asked the AI to do, where it helped, where it got things wrong, and how you reviewed, corrected, and made the final calls.
We care less about how big the prototype is and more about how you think, how you work with AI, and how honestly you can describe your own process.
What You'll Learn
- End-to-end full-stack development the AI-native way.
- How to embed AI assistants into the SDLC — planning, coding, reviews, tests, and docs.
- How to use AI assistants effectively and responsibly — knowing when to trust their output and when to review it closely.
- How to build and validate MVPs quickly and iterate on real feedback.
- Working in an Agile environment: version control, code reviews, debugging, and deployment best practices.
- Exposure to production-grade applications and modern engineering standards.
We value how you think and learn over how many tools you already know. If you're a strong builder who is excited to work alongside AI, we want to hear from you.
Additional Information: Candidates are responsible for safeguarding sensitive company data against unauthorized access, use, or disclosure, and for reporting any suspected security incidents in line with the organization's ISMS (Information Security Management System) policies and procedures.