Role & Responsibilities

- Develop and maintain Python-based backend applications using FastAPI or Flask.

- Build practical Generative AI applications using LLMs, prompt engineering, embeddings, and context management.

- Develop RAG (Retrieval-Augmented Generation) pipelines, including document ingestion, chunking, embeddings, retrieval, and response generation.

- Build basic AI Agent and Agentic AI workflows using LangChain or LangGraph.

- Implement tool calling, API integrations, and REST APIs for AI-powered applications.

- Work with vector databases such as FAISS, ChromaDB, Pinecone, or similar technologies.

- Work with PostgreSQL/MySQL and basic NoSQL databases.

- Develop clean, reusable, and maintainable Python code following OOP and coding best practices.

- Use Docker, Git/GitHub, unit testing, logging, and debugging practices.

- Deploy and support applications on AWS or other cloud platforms.

- Test, debug, and troubleshoot backend and GenAI applications.

- Use AI coding assistants such as Claude, Cursor, GitHub Copilot, or similar tools effectively.

- Collaborate with the development team to design, develop, test, and deliver AI-powered solutions.

- Take ownership of assigned tasks and continuously learn emerging GenAI and Agentic AI technologies.





Preferred Candidate Profile

- 1 2 years of hands-on experience in Python/backend development or AI/GenAI application development.

- Strong knowledge of Python, OOP, data structures, and backend development.

- Hands-on experience with FastAPI or Flask and REST API development.

- Practical understanding of LLMs, Generative AI, prompt engineering, and embeddings.

- Experience building RAG applications and working with vector databases.

- Familiarity with LangChain or LangGraph, AI agents, workflows, and tool calling.

- Knowledge of PostgreSQL/MySQL and basic NoSQL concepts.

- Basic experience with AWS or other cloud platforms.

- Familiarity with Docker and Git/GitHub.

- Solid problem-solving, debugging, communication, and analytical skills.

- Ability to understand existing code, troubleshoot issues, and build features independently.

- Experience using AI-assisted coding tools such as Cursor, Claude, or GitHub Copilot is preferred.

- Candidates should have practical project experience, not just theoretical knowledge of GenAI concepts.

- Strong willingness to learn, adapt, and work across Python backend and GenAI technologies.

📌 AI Engineer / GenAI Backend Developer (Chennai)
🏢 Bitcot Technologies
📍 Chennai