Join EY and shape your future with confidence by contributing to a better working world. As part of Global Delivery Services, you'll be instrumental in supporting EY's growth agenda. Our innovation specialists bring together environments, technologies, and skilled teams to foster rapid prototyping and innovative thinking. This role focuses on leveraging AI and AIOps to enhance CloudOps within the Azure ecosystem.

We are seeking a Senior Cloud DevOps Engineer with extensive Azure expertise and a strong background in applying AI to CloudOps. You will be responsible for end-to-end infrastructure automation, CI/CD pipeline engineering, and incident resolution. A key aspect of this role involves utilizing generative AI and AIOps for improved observability, faster triage, accurate root cause analysis, automated runbooks, and overall operational efficiency. You will lead technical escalations, architect secure AI-driven operations, and collaborate across various teams to ensure highly available services.

You will manage critical Azure Kubernetes Service (AKS) clusters, including design, deployment, and optimization for high availability and cost-efficiency. This includes implementing secure networking, workload identities, and governance policies. A significant part of your role will involve developing reusable infrastructure-as-code (IaC) using ARM Templates and Bicep for automated, standardized deployments across environments.

Architecting and implementing robust CI/CD pipelines within Azure DevOps is essential, focusing on automation across build, release, testing, and deployment. You will also design and implement Azure Landing Zones aligned with the Microsoft Cloud Adoption Framework (CAF), establishing foundational architecture for identity, networking, and governance. Experience with Terraform and Terraform Cloud will be vital for provisioning and managing Azure infrastructure consistently and securely.

A core responsibility is the design and implementation of AI-enabled CloudOps workflows. This includes building and operating secure cloud operations agents using tools like Microsoft Foundry and Azure OpenAI for alert enrichment, incident triage, root cause analysis, and knowledge retrieval. You will develop retrieval-augmented generation (RAG) solutions and engineer production controls for security, auditability, and responsible AI practices. Monitoring AI services for performance, cost, and operational risk using Azure Monitor and Application Insights will also be key.

We require 5-8 years of experience in DevOps, cloud infrastructure operations, and automation, with a proven track record in building and deploying highly available Azure cloud environments. Proficiency in Kubernetes, Terraform, CI/CD tooling, and automation scripting is essential.

Demonstrated experience in delivering at least one AI-enabled CloudOps, DevOps, SRE, or observability use case from design to production support is expected. Familiarity with scripting languages like Bash and Python, along with a deep understanding of Azure services such as VMs, Blob Storage, AKS, and AAD, is crucial. Experience with container orchestration using Kubernetes, Helm, and Docker, alongside configuration management tools like Ansible, is necessary.

Strong knowledge of cloud security best practices, IAM policies, and compliance standards is mandatory. Experience with ITSM tools like ServiceNow for incident and change management is required. A practical understanding of generative AI concepts, including prompt engineering, embeddings, vector databases, RAG, agentic workflows, and function calling, within an enterprise operations context is vital. Hands-on Python experience for API integration and automation is also a must.