Key Responsibilities:

- Design, develop, and deploy enterprise-grade Generative AI applications using Python.

- Build and optimize Retrieval-Augmented Generation (RAG) pipelines for knowledge-based AI systems.

- Develop AI-powered chatbots, virtual assistants, and intelligent automation solutions.

- Integrate and customize Large Language Models (LLMs) for enterprise use cases.

- Implement advanced Natural Language Processing (NLP) techniques for text analysis and language understanding.

- Develop AI workflows using LangChain, LangGraph, or similar orchestration frameworks.

- Build REST APIs and integrate AI services with enterprise applications.

- Optimize prompt engineering, embeddings, vector search, and retrieval strategies.

- Monitor, evaluate, and continuously improve AI model performance, accuracy, and scalability.

- Collaborate with data scientists, software engineers, and business stakeholders to deliver AI-driven solutions.

Required Skills :

- Strong proficiency in Python programming.

- Hands-on experience with Large Language Models (LLMs) such as GPT, Llama, Claude, or Gemini.

- Strong knowledge of Natural Language Processing (NLP) concepts and libraries.

- Experience designing and implementing Retrieval-Augmented Generation (RAG) pipelines.

- Hands-on experience with LangChain, LangGraph, or similar AI orchestration frameworks.

- Experience with prompt engineering, embeddings, vector databases, and semantic search.

- Knowledge of AI frameworks such as Hugging Face Transformers, OpenAI SDK, or similar.

- Experience developing REST APIs and integrating AI services into enterprise applications.

- Strong analytical, debugging, and problem-solving skills.

Preferred Skills :

- Experience with vector databases such as Pinecone, ChromaDB, FAISS, Weaviate, or Milvus.

- Familiarity with cloud platforms such as AWS, Azure, or GCP and AI services.

- Knowledge of Docker, Kubernetes, CI/CD, and MLOps practices.

- Experience with Git, Agile/Scrum methodologies, and DevOps workflows.

- Exposure to AI agent frameworks, multi-agent systems, and model evaluation techniques is an added advantage.