Principal Cloud Engineer (Azure)

Role Overview: The Principal Cloud Engineer (Azure) will be responsible for leading Cloud Operations, FinOps, SecOps, and AI-driven automation initiatives across enterprise-scale Azure environments. The ideal candidate has deep, hands-on expertise in managing complex Azure estates, implementing automation, and delivering measurable outcomes in cost, security, and performance. The candidate should also bring practical experience in designing and operationalizing Generative AI workloads in Azure using services such as Azure OpenAI and Cognitive Services. Key Responsibilities: Cloud Operations and Governance- Operate and optimize large-scale Azure environments across multiple subscriptions and regions Build and manage Azure Landing Zones using Terraform, or ARM templates Enforce governance policies through Azure Policy, Blueprints, and Role-Based Access Control (RBAC) Lead reliability improvements, incident response management, and operational runbook standardization FinOps Execution - Drive cost optimization through workload analysis, rightsizing, reservations, and custom policies Build dashboards integrating Azure Cost Management and budgets for real-time insights Collaborate with finance and business teams for accurate forecasting, budgeting, and internal chargebacks Document and report tangible cloud cost savings across projects and business units. Security and Compliance - Improve cloud security posture using Microsoft Defender for Cloud, Security Center, and Sentinel Implement automated security policies, JIT access, and conditional access controls Remediate vulnerabilities, enforce encryption, and drive compliance with frameworks like CIS, NIST, and ISO Automation and Tooling- Build automation for routine operational tasks using PowerShell, Azure CLI, and Azure Automation Develop Infrastructure as Code modules to standardize environment provisioning Implement event-driven automation using Azure Logic Apps, Functions, and DevOps/GitHub workflows Generative AI and Emerging Technologies (Nice to have) - Design, deploy, and manage Generative AI applications using Azure OpenAI Service and Azure Cognitive Services Build and secure AI-driven workflows for content generation, summarization, and customer service automation Implement responsible AI principles and ensure compliance with data governance policies Orchestrate AI-powered processes using Logic Apps, Azure Functions, and custom connectors for end-to-end automation Partner with internal teams to turn AI prototypes into production-grade, secure, and cost-effective solutions Cross-Functional Collaboration - Lead CCoE initiatives, establish operational excellence, and develop repeatable cloud practices Align operations, security, cost, and AI strategies with product and business goals Provide insights and recommendations for platform improvements and product roadmap alignment Desired Skills Must Have: Experience operating within Azure-focused MSPs or enterprise Cloud Centers of Excellence Proven ownership of Azure environments with over $1 million in annual cloud spend Hands-on deployment and management of Azure Lighthouse for multi-tenant or business unit-level delegation Demonstrated results in achieving 30% or more cost optimization and measurable improvements in operational KPIs Prior experience deploying GenAI models or services on Azure and securing AI workloads in production Deep understanding of Azure-native tools: Virtual Machines, Networking, Storage, Monitor, Defender, Azure Policy Experience with Azure Lighthouse and multi-subscription management Proficiency in PowerShell, Azure CLI, and Infrastructure as Code using Terraform or Bicep Hands-on experience with Azure OpenAI or Cognitive Services in production or pilot projects Experience operationalizing AI workloads, including cost, scaling, and access control considerations Strong collaboration, documentation, and leadership skills across cross-functional teams. Preferred Skills Experience with third-party tools like CloudHealth, Apptio Cloudability, or Wiz Familiarity with Azure Arc, Stack HCI, or hybrid cloud scenarios Exposure to Azure ML, Azure AI Studio, or custom GPT deployments Strong understanding of Responsible AI and AI security governance principles Experience 12+ years of experience on cloud platforms, with a specialty in Azure. 6 - 7 years of experience in Azure CloudOps and FinOps . Education Bachelor’s or master’s degree in computer science, Engineering, Business, or a related field.