AI-Native Full Stack Engineer
Summary
Builds production-quality web applications end to end on a MERN or Python stack — React/Next.js frontend, Node.js or Python backend, and any suitable database — while using AI coding tools like Claude, Copilot, Codex, and Cursor for planning, coding, testing, refactoring, and documentation. Role requires 6-8 years of experience and is based in India.
AI-Native Full Stack Engineer
Role Title: AI-Native Full Stack Engineer
Stack: MERN or Python Full Stack
Experience: 6-8 years
Role Summary
We are looking for an AI-native Full Stack Engineer who can build production-quality applications using MERN or Python full stack technologies and effectively use AI engineering tools to improve development speed, quality, testing, and documentation.
Key Responsibilities
- Build frontend, backend, APIs, data access, and integrations.
- Work with React/Next.js and either Node.js or Python backend services.
- Use any suitable database based on project needs.
- Use Claude, Copilot, Codex, Cursor, or similar tools for planning, coding, debugging, testing, refactoring, and documentation.
- Follow AGENTS.md, coding standards, prompts, skills, hooks, and AI-assisted development workflows.
- Write unit tests, integration tests, API tests, and basic UI tests.
- Participate in code reviews and validate AI-generated code.
- Support deployment, troubleshooting, logging, monitoring, and configuration.
- Apply basic LLM and prompt engineering concepts where required.
Required Skills
- Strong JavaScript/TypeScript or Python programming skills.
- Experience with React or Next.js.
- Backend experience with Node.js, Express/NestJS, FastAPI,, or Flask.
- Experience with any database: PostgreSQL, MySQL, MongoDB, SQL Server, Oracle, Redis, or similar.
- Good understanding of REST APIs, authentication, authorization, validation, and error handling.
- Experience with Git, pull requests, testing, debugging, and CI/CD basics.
- Basic cloud exposure in AWS, Azure, or GCP.
- Practical usage of AI coding tools such as Claude, Copilot, Codex, Cursor, or similar.
- Basic understanding of LLMs, prompts, RAG, embeddings, and AI application patterns.