Retrieval-Augmented Generation (RAG), Large Language Models (LLM), Docker, FastAPI, Azure, Python, Kubernetes, LangChain, AWS Bedrock, AI Agent Development, HuggingFace, MLflow, Pinecone, Vector Databases, Vertex AI, ChromaDB, OpenAI, Weaviate, Embedding Models, Prompt Engineering, LlamaIndex

Data Quality, Data Modelling, PostgreSQL, Elasticsearch, Spark, Python, Kubernetes, Data Processing, CI/CD, Microsoft Fabric, metadata

.Net Core, C#, Microsoft Technologies, Web Apis, AWS, Apis, REST, Gcp, Azure, Kubernetes, AI ML fundamentals, Azure OpenAI, Relational Databases, LLM usage patterns, AI-enabled features, non-relational databases, guardrails, AI-assisted coding tools, vector search embeddings, responsible AI practices, output validation, AWS GCP AI services, containerization technologies, messaging systems, cloud environments, OpenAI, SDKs, prompt design

Apis, Unit Testing, Node.js, Microservices, React, Integration Testing, automation, orchestration platforms, GraphQL APIs, AI LLM capabilities, CI CD practices, agentic frameworks