Senior Azure Cloud Engineer

Quick Facts

• Role: Senior Azure Cloud Engineer

Description

Design, build, automate, and operate secure, scalable, cost-efficient cloud solutions on Microsoft Azure. You will work hands-on with Azure infrastructure, containers, DevOps pipelines, Infrastructure as Code, observability, security controls, and AI-enabled cloud solutions. You’ll translate architecture standards into reusable deployment patterns and production-ready services.

Responsibilities

• Design, implement, and maintain Azure cloud infrastructure (subscriptions, resource groups, networking, identity, governance, security, platform services)

• Build and support reusable Azure deployment patterns for microservices, containers, serverless, data integrations, and AI-enabled solutions

• Implement and operate Azure Kubernetes Service environments (node pools, ingress, workload identity, secrets management, autoscaling, monitoring, container registry integration, security controls)

• Build, maintain, and improve Infrastructure as Code using Terraform (reusable modules, multi-environment deployments, automated validation, CI/CD integration)

• Design and implement CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar tools

• Apply DevOps practices: automated builds/testing, security scanning, artifact management, environment promotion, deployment approvals, rollback strategies, and release automation

• Use GitHub Copilot and AI-assisted tools to improve scripting, IaC, pipeline creation, code review, troubleshooting, documentation, and automation

• Implement cloud-native solutions with Azure services (App Service, Azure Functions, Logic Apps, Event Grid, Service Bus, Storage, Key Vault, API Management, Azure SQL, Cosmos DB, Azure Monitor, Application Insights)

• Support AI-enabled solutions using Azure AI services (Azure AI, Azure OpenAI, Azure AI Search, Azure Machine Learning)

• Build AI architecture components and patterns (RAG, agentic workflows, multi-agent orchestration, tool/function calling, prompt management, grounding, evaluation, responsible AI controls)

• Implement secure integration patterns (managed identities, RBAC, private endpoints, private DNS, NSGs, firewalls, API gateways)

• Establish observability and operations (Azure Monitor, Log Analytics, Application Insights, dashboards, alerts, distributed tracing, operational runbooks)

• Troubleshoot complex incidents and optimize performance, reliability, scalability, and cost efficiency

• Apply DevSecOps practices (secrets management, dependency scanning, container image scanning, policy validation, secure configuration, compliance automation)

• Contribute to standards, templates, documentation, and platform engineering; provide technical guidance, mentoring, and code reviews

• Partner with architects and stakeholders to deliver practical, secure, maintainable Azure implementations

Requirements

• Strong hands-on experience designing, implementing, and operating Azure cloud solutions in enterprise environments

• Solid understanding of Azure networking, identity, governance, security, monitoring, and platform services

• Practical experience with Azure Landing Zone concepts, including hub-and-spoke networking, private endpoints, private DNS, firewalls, NSGs, route tables, and workload integration patterns

• Hands-on experience with Azure Kubernetes Service, containers, container registries, ingress controllers, workload identity, autoscaling, monitoring, and container security

• Strong experience with Terraform (module development, state management, validation, multi-environment delivery)

• Strong experience with CI/CD pipelines (preferably GitHub Actions, Azure DevOps, GitLab CI/CD, or similar)

• Understanding of DevSecOps practices including automated testing, security scanning, artifact management, release automation, and deployment governance

• Experience with GitHub workflows (pull requests, code reviews, branching strategies)

• Practical experience using AI-assisted engineering tools such as GitHub Copilot

• Experience with Azure PaaS and integration services (App Service, Azure Functions, Logic Apps, API Management, Event Grid, Service Bus, Storage, Key Vault, Azure SQL, Cosmos DB)

• Experience implementing observability (Azure Monitor, Log Analytics, Application Insights, Container Insights, dashboards, alerting, runbooks)

• Understanding of Azure AI and generative AI services, especially Azure OpenAI, Azure AI Search, and AI-enabled automation patterns

• Knowledge of AI patterns such as RAG, agentic workflows, multi-agent systems, tool/function calling, grounding, prompt management, evaluation, and responsible AI

• Ability to troubleshoot complex issues across cloud infrastructure, networking, containers, CI/CD, security, and application integrations

• Scripting and automation skills using PowerShell, Bash, Python, or similar languages

• Ability to work independently and take ownership in production-grade environments

• Strong communication skills working with architects, engineers, security teams, product teams, and business stakeholders