Backend AI Engineer

Responsibilities:

• Build and integrate AI-powered applications using LLMs and generative AI technologies.
• Work on LLM-based applications, AI agents, and intelligent automation solutions.
• Develop and implement RAG (Retrieval-Augmented Generation) pipelines.
• Work with LLM APIs such as OpenAI, Gemini, Claude, or similar models.
• Explore and implement prompt engineering techniques to improve AI output quality.
• Work with vector databases and embeddings for semantic search and information retrieval.
• Experiment with AI frameworks such as LangChain and LangGraph.
• Evaluate, test, and optimize AI models and applications for performance and accuracy.
• Develop and maintain backend services and REST APIs using Python and FastAPI.
• Build scalable and efficient backend components to support AI-powered applications.
• Integrate third-party APIs, databases, and AI services.
• Write clean, reusable, and maintainable code.
• Debug issues and optimize application performance.

Requirements:

• 1-2 years of hands-on experience in Python development.
• Strong understanding of Python programming fundamentals.
• Hands-on experience with FastAPI and REST API development.
• Practical exposure to generative AI and large language models (LLMs).
• Understanding of prompt engineering, embeddings, and RAG concepts.
• Experience integrating LLM APIs such as OpenAI, Gemini, or Claude.
• Familiarity with LangChain, LangGraph, or similar AI frameworks.
• Basic understanding of SQL/NoSQL databases and vector databases.
• Good problem-solving and debugging skills.
• Ability to learn and work with emerging AI technologies.
• Genuine interest in building AI-first products.
• Strong hands-on implementation skills rather than only theoretical knowledge.
• Ability to experiment, prototype, and take ownership of assigned tasks.

Good To Have:

• Experience building AI agents or agentic workflows.
• Exposure to vector databases such as Pinecone, Qdrant, ChromaDB, or FAISS.
• Familiarity with Docker, Git, and cloud platforms.
• Experience with asynchronous programming in Python.
• Understanding of AI evaluation, hallucination reduction, and model optimization.