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.