Azure MLOps Trainer Needed for Training Sessions

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)