Azure MLOps Trainer Needed for Training Sessions We are hiring a senior Azure AI engineer to provide structured, hands-on training in building enterprise-grade LLM systems. This is NOT a beginner AI course and NOT a chatbot project. We need practical training in implementing: - Azure OpenAI API integrations (production-ready) - Full RAG pipelines using Azure AI Search (vector + hybrid search) - Document ingestion workflows (Blob > OCR > chunking > embeddings) - Function/tool-calling for agentic workflows - Secure deployment using Azure Functions / Container Apps / AKS - Logging, retries, structured validation, and reliability patterns - Enterprise constraints (RBAC, private endpoints, managed identity) The focus is: - Clean architecture - Production patterns - Observability - Error handling - Performance considerations - Cost control No research discussions. No generic prompt engineering. No UI demos. No theory-only explanations. You must have shipped real Azure LLM systems into production. Deliverables: - Structured training roadmap - Live coding sessions - Architecture walkthroughs - Code review of implementations - Capstone: Enterprise RAG + agent workflow deployed on Azure Required Experience: - Azure OpenAI (production) - Azure AI Search with vector search - Azure Document Intelligence or equivalent OCR - LLM function/tool calling - Python backend development (FastAPI preferred) - Azure DevOps or GitHub Actions - Observability (App Insights / structured logging) - Secure Azure deployments (Managed Identity, RBAC)