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).
• Excellent communication skills, with the ability to translate architecture decisions for both technical and executive audiences.