AI Data Engineer

Key Responsibilities AI & LLM Integration Design and implement LLM-based workflows , including RAG (Retrieval-Augmented Generation) pipelines. Build agentic orchestration frameworks using tools such as LangChain, LangGraph, CrewAI , or similar. Integrate vector databases and embeddings for semantic search and AI-driven applications. Data Engineering & Pipelines Design, develop, and maintain scalable, reliable data pipelines using Python and Azure services . Implement ETL/ELT workflows for structured and unstructured data. Optimize data ingestion, transformation, and storage for performance and cost efficiency. Cloud & Deployment Deploy data and AI solutions using cloud-native architectures on Azure (preferred) or AWS/GCP . Containerize applications using Docker and orchestrate using Kubernetes . Implement CI/CD pipelines for automated build, test, and deployment.