About the role
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.