TechOps-CloudOps-Azure-DevOps-Senior

The opportunity

We are looking for a skilled Senior Cloud DevOps Engineer with deep expertise in the Azure cloud platform and experience applying AI to CloudOps. This role is responsible for end-to-end infrastructure and deployment automation, CI/CD engineering, reliability, and incident resolution, while using generative AI and AIOps capabilities to improve observability, triage, root cause analysis, runbook automation, and operational efficiency. The role will lead escalations, design secure and governed AI-enabled operations solutions, and collaborate with engineering, infrastructure, security, data, and AI teams to deliver highly available services.

Your key responsibilities

• Responsible for decision-making, optimizing processes, resource management, and overseeing team management as needed for task execution.
• Accountable for allocating personnel, supervising team members, assigning tasks, ensuring that the team has the necessary tools and support to succeed in their roles and optimizing and evaluating their performance to meet organizational goals.
• Azure Kubernetes Service (AKS)
• Design, deploy, and manage scalable AKS clusters for mission‑critical workloads.
• Implement secure cluster networking, workload identities, and governance policies.
• Optimize AKS performance, reliability, and cost as part of the platform architecture.
• Integrate AKS with CI/CD pipelines, GitOps workflows, and monitoring solutions.
• ARM Templates & Bicep
• Develop reusable ARM/Bicep infrastructure‑as‑code templates for automated deployments.
• Standardize resource deployments through parameterized and modular Bicep templates.
• Migrate legacy ARM templates to Bicep for improved maintainability.
• Ensure consistency, compliance, and repeatability across environments using IaC best practices.
• Azure DevOps
• Architect and implement end‑to‑end CI/CD pipelines for applications and infrastructure.
• Lead DevOps automation initiatives across build, release, testing, and deployment workflows.
• Implement secure DevOps practices, including secrets management and pipeline governance.
• Manage Azure Repos, Boards, Pipelines, Artifacts, and environment configurations.
• Landing Zone Architecture
• Design and implement Azure Landing Zones aligned with Microsoft Cloud Adoption Framework (CAF).
• Define foundational architecture for identity, networking, governance, policies, and management groups.
• Build scalable enterprise-ready landing zones for multi‑subscription and multi‑environment setups.
• Implement guardrails such as Azure Policies, RBAC structures, and blueprint‑style templates.
• Terraform & Terraform Cloud
• Develop and manage Terraform modules for consistent provisioning across environments.
• Implement Terraform Cloud/Enterprise for remote state management and secure pipelines.
• Automate Azure infrastructure deployments using version-controlled IaC.
• Enforce policies, workspaces, and governance using Terraform Cloud capabilities.
• AI-enabled CloudOps & Agentic Automation
• Design and implement AI-assisted operational workflows for alert enrichment, incident triage, event correlation, root cause analysis, knowledge retrieval, and runbook execution.
• Build and operate secure cloud operations agents using Microsoft Foundry, Azure OpenAI, Foundry Agent Service, Azure AI Search, and orchestration frameworks such as Microsoft Agent Framework or Semantic Kernel.
• Develop retrieval-augmented generation (RAG) solutions grounded in approved runbooks, knowledge articles, telemetry, and configuration data; apply vector, hybrid, and semantic search patterns.
• Integrate agents securely with operational tools and APIs using function calling and Model Context Protocol (MCP), with approval gates for production actions.
• Engineer production controls for identity, private networking, secrets, prompt-injection defence, data protection, content safety, auditability, evaluation, and responsible AI.
• Monitor AI services and agents for availability, latency, quality, token usage, model drift, cost, and operational risk using Azure Monitor, Application Insights, OpenTelemetry, and enterprise observability platforms.
• Documentation & Best Practices
• Create detailed architectural documents, design specs, deployment guides, and runbooks.
• Maintain IaC repositories with clear documentation, versioning, and conventions.
• Conduct knowledge transfer sessions, workshops, and technical enablement for teams.
• Provide guidance on DevOps, cloud governance, scalability, cost optimization, and security best practices.

Skills and attributes for success

• Hands-on experience with CI/CD tools like GitHub Actions, Azure DevOps Pipelines,
• Expertise in Infrastructure as Code (IaC) using Terraform; good understanding of ARM Templates/ Biceps.
• Familiarity with scripting languages such as Bash and Python.
• Deep understanding of Azure services(VMs, Blob Storage, AKS, AAD).
• Container orchestration and management using Kubernetes, Helm, and Docker.
• Experience with configuration management and automation tools such as Ansible.
• Strong understanding of cloud security best practices, IAM policies, and compliance standards.
• Experience with ITSM tools like ServiceNow for incident and change management.
• Practical understanding of generative AI, large language models, prompt engineering, embeddings, vector databases, vector search, RAG, agentic workflows, tool/function calling, and MCP in an enterprise operations context.
• Hands-on Python experience for API integration, telemetry processing, automation, evaluation, and AI-enabled operational tooling.
• Ability to design human-in-the-loop automation with least-privilege access, measurable quality thresholds, rollback controls, audit trails, and safe failure handling for production environments.
• Strong documentation and communication skills.

To qualify for the role, you must have

• 5 - 8 years of experience in DevOps, cloud infrastructure operations, and automation.
• Hands-on expertise in Building and deploying Azure cloud environments for high availability systems.
• Proficiency in Kubernetes, Terraform, CI/CD tooling, and automation scripting.
• Demonstrated experience delivering at least one AI-enabled CloudOps, DevOps, SRE, observability, service-management, or knowledge-assistant use case from design through production support.
• Experience in a 24x7 rotational support model.
• Relevant certifications in Azure (e.g., Azure Solutions Architect Expert, DevOps Engineer Expert).

Technologies and Tools

Must have

• Cloud Platforms: Azure
• CI/CD & Deployment: Azure DevOps Pipelines
• Infrastructure as Code: Terraform
• Containerization: Kubernetes (AKS), Docker, Helm
• Logging & Monitoring: Azure Monitor
• Configuration & Automation: Ansible, Bash
• AI-enabled CloudOps: Microsoft Foundry, Azure OpenAI, Foundry Agent Service, Azure AI Search, vector databases, RAG, prompt engineering, tool/function calling, and responsible AI controls
• Programming & Integration: Python, REST APIs, JSON, SDK-based integrations, managed