Azure AI / GenAI Engineer
Experience: 4+ Years
Primary Skills – Azure AI / GenAI (75–80%)
- Azure AI Foundry
- Azure OpenAI / LLM Integration
- AI Agents & Agentic AI Development
- RAG (Retrieval-Augmented Generation) Architectures
- Azure AI Search
- Embeddings & Vector Search
- Prompt Engineering
- Function / Tool Calling
- Python & REST APIs
- Responsible AI, Security & Guardrails
- LLM Evaluation, Monitoring & Observability

Secondary Skills – Azure Data Engineering (20–25%)
- Azure Databricks & PySpark
- Azure Data Factory (ADF)
- Microsoft Fabric / Synapse Analytics
- ADLS Gen2
- Delta Lake / Lakehouse
- SQL & Data Modelling
- Microsoft Purview
- ETL/ELT
- IAM & CI/CD

Primary Requirement
- Candidate must be a hands-on Azure AI/GenAI Engineer capable of developing production-grade Generative AI and Agentic AI solutions.
- Azure AI/GenAI should be the candidate's core expertise.
- Data Engineering should be a secondary capability.




- Pure Data Engineers with only basic GenAI exposure should not be considered.

Vendor Screening Priority
The following skills should form the core skill set:
- Azure AI Foundry
- Azure OpenAI
- Python
- RAG
- Azure AI Search
- Agentic AI

Positive to Have
- Multi-Agent Architectures
- MCP (Model Context Protocol)
- Semantic Kernel
- Azure Functions
- Azure Container Apps / AKS
- Microsoft Fabric
- Relevant Azure AI Certifications

Candidate Evaluation Priority
Must-have/core:
Azure AI Foundry + Azure OpenAI + Python + RAG + Azure AI Search + Agentic AI
Added advantage:
Databricks + ADF + Fabric + Azure Data Engineering
Key screening point: The candidate should primarily be an Azure AI/GenAI Engineer, not a Data Engineer who has limited exposure to GenAI.

📌 Azure AI (Hyderabad)
🏢 HCL INDIA
📍 Hyderabad