WGA Consulting, LLC

Azure Security & Governance Engineer – Microsoft AI Platform

Remote, US$187,200-$249,600Posted 11 days ago

Job Description

About WGA Advisors

WGA Advisors is a global management consulting firm and a world-class alternative to the big-name consulting firms. We help senior leaders make and execute the decisions that matter most across AI and digital transformation strategy, ESG, growth, culture, operations, and enterprise transformation.

Our firm focuses on areas of senior management concern, creating enduring value and delivering measurable impact at the intersection of strategy, technology, and operating model design. WGA’s AI Workforce Solutions practice is at the forefront of helping global enterprises move from isolated AI experimentation to scaled, business-led agentic AI deployment.

The Opportunity

WGA Advisors is engaging an Azure Security & Governance Engineer – Microsoft AI Platform to hands-on design, configure, secure, test, and support the production deployment of an enterprise Microsoft AI Agent platform.

This is a high-impact execution role responsible for implementing the security, identity, governance, networking, data-protection, and monitoring controls surrounding a Microsoft AI environment built using Microsoft Foundry, Microsoft Copilot Studio, Microsoft Power Platform, Microsoft Purview, Microsoft Sentinel, Microsoft Entra ID, Azure Key Vault, and Presidio.

The Azure Security & Governance Engineer will work directly alongside WGA’s Microsoft Azure AI and Power Platform engineering resources, engagement leadership, and enterprise technology and security teams. The role is responsible for turning approved security architecture and governance requirements into configured, tested, documented, and production-ready Microsoft controls.

A major focus of the environment is the protection of personally identifiable information and sensitive enterprise data used by AI Agents. The architecture requires PII to be detected, tokenized or pseudonymized before applicable data is submitted to large language models, with tightly controlled re

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