1. Core Technical
LLM orchestration frameworks: LangChain, Semantic Kernel, Azure AI Foundry
MLOps practices: model versioning, deployment pipelines, monitoring (MLflow, Azure ML)
Prompt engineering: few-shot, chain-of-thought, structured output, retrieval-augmented generation (RAG)
Azure AI Services: Azure OpenAI, Cognitive Services, AI Search (vector and hybrid)
Feature engineering and ML pipeline development (Databricks Feature Store, MLflow)
Responsible AI: bias detection, explainability, AI governance frameworks
AI-ready data design: embedding generation, vector store management, data curation for AI
API integration: exposing AI capabilities as enterprise services (FastAPI, Azure API Management)
2. Certifications
3. Industry & Business Knowledge
4. Behavioral & Leadership