Cloud & AI Security Operations Engineer

Required Cloud & AI Security Operations Engineer
So, whats the role all about?
The Cloud & AI Security Operations Engineer is a hands-on individual contributor responsible for securing our cloud, productivity, and AI ecosystem. Reporting to the Cloud Services & Infrastructure Manager, you will operate and improve security controls across Azure, Microsoft 365, Entra ID, Defender XDR, Microsoft Sentinel, and Microsoft Purview. You will also extend security coverage across our growing AI footprint-including Microsoft 365 Copilot, Copilot Studio, Azure OpenAI, Azure AI Foundry, and emerging agentic workflows-and contribute to security across a smaller AWS estate.
You will partner closely with InfoSec, Cloud Architecture, Privacy, and R&D IT to keep our cloud and AI adoption safe, governed, and scalable. This is primarily a cloud security operations role anchored in the Microsoft ecosystem, with a clear growth path into AI security as the discipline matures.
How will you make an impact?
Strengthen cloud security operations across our cloud estate, with primary focus on Azure infrastructure, including network, workload, storage, secrets, key management, and secure configuration controls.
Use Defender for Cloud to monitor CSPM findings, prioritize remediation, reduce cloud attack surface, and apply consistent security principles across Azure and the smaller AWS environment.
Operate and improve Entra ID security controls, including Conditional Access, PIM, OAuth app governance, service principal hygiene, and Microsoft Graph permission reviews.
Build and tune detections, alerts, and playbooks in Microsoft Sentinel and Defender XDR for cloud misconfiguration, identity attacks, data exfiltration, and endpoint-to-cloud attack paths.
Operate Microsoft Purview capabilities, including DLP, sensitivity labeling, and information protection, to keep sensitive data classified, protected, and auditable across Microsoft 365 and cloud workloads.
Support investigation and containment of cloud, identity, and data incidents, and contribute to post-incident hardening.
Extend security controls to Microsoft 365 Copilot, Copilot Studio, Azure OpenAI, Azure AI Foundry, internal LLM environments, and agentic workflows as AI adoption matures.
Help define practical guardrails for AI usage, including DLP coverage, access controls, monitoring, vendor/plugin review, and detection of misuse or sensitive-data leakage.
Contribute to secure-by-default reference architectures, approved patterns, and enablement sessions that support safe cloud and AI adoption across IT, business, and R&D.