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:

1. Azure AI Foundry

2. Azure OpenAI

3. Python

4. RAG

5. Azure AI Search

6. 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 / GenAI Engineer (Hyderabad)
🏢 HCL INDIA
📍 Hyderabad