Senior Microsoft Cloud Engineer / Cloud Solutions Architect

Key Responsibilities

Azure & M365 Architecture

• Design, architect, and continuously evolve enterprise-scale Azure infrastructure (networking, compute, storage, identity, governance, cost management) across multiple subscriptions/tenants.
• Own end-to-end architecture of Microsoft 365 workloads (Exchange Online, SharePoint/OneDrive, Teams, Entra ID, Intune, Purview) - not just administration, but strategic design of information architecture, compliance boundaries, and collaboration models.
• Define and enforce landing zone, hub-and-spoke, and hybrid identity architectures aligned to Microsoft Cloud Adoption Framework (CAF) and Well-Architected Framework (WAF) principles.
• Lead Infrastructure-as-Code strategy (Bicep, ARM, Terraform) and CI/CD pipelines for cloud resource deployment.
• Architect disaster recovery, business continuity, and high-availability solutions across Azure and M365 workloads.

Security & Governance

• Design and implement Zero Trust architecture across identity (Entra ID / Conditional Access), network, endpoint, and data layers.
• Own Microsoft security stack architecture: Defender for Cloud, Defender for Endpoint/Identity/Office 365, Sentinel (SIEM/SOAR), Purview (DLP, information protection, insider risk).
• Establish governance frameworks for cost management, tagging, RBAC/PIM, policy-as-code (Azure Policy), and regulatory compliance (SOC 2, ISO 27001, GDPR as applicable).
• Ensure security-by-design principles are baked into every AI and data platform deployment.

AI Solutions Deployment

• Architect and deploy AI/LLM solutions across the cloud environment — including Microsoft Copilot (M365 Copilot, Copilot Studio), Azure AI Foundry / Azure OpenAI Service, and third-party model providers such as Claude (Anthropic).
• Design secure integration patterns for AI tools: data access boundaries, prompt/data governance, network isolation, logging/auditing, and identity-aware access controls.
• Build and maintain retrieval-augmented generation (RAG) pipelines, agentic workflows, and AI-assisted automation connected to enterprise data sources.

Data Platform Administration

• Administer and architect modern data platforms — Snowflake and/or Databricks — including workspace/account setup, access control, cost governance, performance tuning, and integration with Azure data services (Data Factory, Synapse, Fabric, Data Lake).
• Design secure, well-governed data pipelines that feed AI/analytics workloads while maintaining data lineage, quality, and compliance.
• Partner with data engineering/analytics teams to ensure the cloud and data architecture support scalable AI and BI initiatives.

Leadership & Collaboration

• Act as the subject-matter authority on Microsoft cloud architecture for engineering, security, and business stakeholders.
• Mentor junior cloud/systems administrators and elevate the team's overall cloud maturity.
• Own technical documentation, architecture decision records (ADRs), and runbooks.
• Stay current with the rapidly evolving Microsoft, AI, and data platform landscape and proactively recommend improvements.

Required Qualifications

• 8+ years of experience in cloud infrastructure engineering, with 5+ years focused specifically on Microsoft Azure and Microsoft 365 at an architecture/design level (not just administration).
• Demonstrated experience designing and architecting (not just maintaining) enterprise Azure environments: networking (VNets, ExpressRoute, VPN, Azure Firewall), compute (VMs, AKS, App Service, Functions), storage, and identity (Entra ID, hybrid identity, Conditional Access, PIM).
• Deep expertise across the M365 stack: Exchange Online, SharePoint/OneDrive, Teams, Purview, Intune, and Entra ID, including complex migrations and tenant-to-tenant architecture.
• Strong background in cloud security architecture: Zero Trust, Defender suite, Sentinel, network segmentation, and compliance frameworks.
• Proven experience deploying AI/LLM-based solutions in an enterprise setting, with an understanding of secure architecture patterns for AI (data governance, access control, model integration).
• Hands-on administration experience with at least one modern data/AI platform: Snowflake or Databricks.
• Strong Infrastructure-as-Code skills (Bicep, Terraform, or ARM templates) and scripting (PowerShell, Python, or similar). xhyhwjd
• Excellent communication skills, with the ability to translate architecture decisions for both technical and executive audiences.

The experience expected from applicants, as well as additional skills and qualifications needed for this job are listed below.