Responsibilities
Frontend for AI Products: Build and maintain responsive, high-quality web interfaces (React / [protected info], TypeScript).
AI-Assisted Engineering: Use AI coding tools (Claude Code, Cursor, GitHub Copilot) effectively within a spec-first workflow to accelerate development while maintaining code quality.
Spec-Driven Development: Work from written specifications (PRDs, technical specs, API contracts) to implement features; contribute to writing and reviewing specs, acceptance criteria, and test cases before coding begins.
Full SDLC Participation: Take part in every stage of the software lifecycle, from requirement analysis, design, and implementation to code review, testing, deployment, and post-release monitoring.
Quality & Testing: Write unit and integration tests (Jest, Vitest, Playwright), and make sure every feature meets its spec and acceptance criteria.
🎯 Requirements
Technical Background: Currently pursuing or holding a degree in IT, Software Engineering, Computer Science, or related fields.
Frontend Fundamentals: Solid grasp of HTML, CSS, and JavaScript/TypeScript; hands-on experience with at least one modern framework (React, [protected info], or Vue).
SDLC Understanding: Clear understanding of the software development lifecycle and common methodologies (Agile/Scrum), including requirements, design, implementation, testing, deployment, and maintenance.
Spec-First Mindset: Ability to read and follow technical specifications precisely, break them into tasks, and raise ambiguities or gaps before implementation.
AI/LLM Awareness: Basic understanding of how LLMs work, prompt engineering, and how to call AI APIs from an application.
Engineering Practices: Familiarity with Git workflows (branching, pull requests, code review) and REST/GraphQL API consumption.
Infrastructure Knowledge: Familiarity with Docker, CI/CD.
⭐ Nice to Have
Experience with UI libraries and design systems (Tailwind CSS, shadcn/ui, Material UI) and turning Figma designs into code.
Working knowledge of at least one backend language and framework, such as Java (Spring Boot), Python (FastAPI / Django), [protected info] (Express / NestJS), or Go (Gin / Echo), to collaborate across the stack when needed.
Familiarity with cloud platforms (GCP/AWS/Azure).
Experience writing technical documentation, specs, or ADRs (Architecture Decision Records).
🎁 Benefits
Cutting-edge Technology Exposure: Build real products on top of the most advanced LLMs and modern AI
developer tooling.
Career Growth: Structured training roadmap to become a professional AI Software Engineer with mentorship on engineering best practices and spec writing.
Work Environment: Young, dynamic culture with a disciplined spec-driven process that still encourages experimentation (fail fast, learn fast).
Compensation: Competitive internship salary.