Azure AI Engineer

Role Overview

An Azure AI Foundry AI Engineer designs, builds, and deploys intelligent generative AI, agentic workflows, and RAG (Retrieval-Augmented Generation) applications. This role requires coding with Python, orchestrating AI models, and adhering to responsible AI standards for enterprise scalability.

Key Responsibilities

• Design autonomous or semi-autonomous AI agents and RAG pipelines using Azure AI Foundry (formerly Azure AI Studio).
• Build and fine-tune large language models (LLMs) and integrate them with business applications, Copilot Studio, and data pipelines.
• Implement performance and evaluation tooling (such as RAGAS or TruLens) to assess grounding accuracy, reduce hallucinations, and ensure model explainability.
• Develop scalable AI infrastructure and maintain reusable AI components in accordance with engineering best practices (version control, observability, CI/CD).

Core Requirements & Skills

• Microsoft Certified: Azure AI Engineer Associate or the Azure AI Apps and Agents Developer Associate certification required with certification link in resume.
• Proficiency in Python, prompt engineering, and utilizing frameworks like LangChain, Semantic Kernel, or crewAI.
• Deep understanding of the Microsoft Azure ecosystem, including Azure OpenAI Service, Azure Machine Learning, and Microsoft Fabric.
• Strong focus on Responsible AI and Model Context Protocol (MCP) to ensure security, privacy, and fairness in model outputs.
• Typically requires a bachelor’s degree in computer science or a related field.
• 2-5+ years of software or AI/ML engineering experience.