About the role
Responsibilities:
- Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs).
- Build AI-powered applications leveraging OpenAI, Azure OpenAI, Claude, Gemini, or other foundation models.
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines.
- Design and implement AI agents using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or LlamaIndex.
- Fine-tune prompts and improve model performance through prompt engineering.
- Integrate AI solutions with enterprise applications using APIs and microservices.
- Work closely with data scientists, product teams, and business stakeholders to deliver AI-driven use cases.
Requirements:
- Strong programming experience in Python.
- Hands-on experience with LLMs, generative AI, and agentic AI.
- Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, and Semantic Kernel.
- Knowledge of Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS, Azure AI Search).
- Experience with RAG architecture and prompt engineering.
- Understanding of REST APIs, microservices, and cloud platforms (Azure/AWS/GCP).
- Familiarity with Docker, Git, CI/CD pipelines.
Preferred Skills:
- Fine-tuning and model evaluation.
- Knowledge Graphs.
- Multi-Agent Systems.
- MLOps and LLMOps.
- Experience with Azure AI Services.