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Mid-level generalist Azure role with recognized employer and broad skill requirements increases applicant competition.
Cloud and Azure skills transfer across industries, but Azure and GenAI specificity requires cloud-domain experience.
Explicit 5–8 years and many mandatory Azure, DevOps, and AI skills make filtering strict.
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Design, develop, deploy, and support end-to-end Azure cloud solutions focusing on AI-first, cloud-enabled, and automation-driven approaches using pro-code (C#, Python, JavaScript/TypeScript) and Azure AI capabilities.
Build and maintain cloud-native applications and services using Azure technologies such as App Service, Functions, Container Apps, AKS, Azure SQL, Cosmos DB, Service Bus, Event Grid, and Event Hubs with emphasis on scalability, security, and maintainability.
Implement DevOps practices including CI/CD pipelines, containerization, infrastructure as code, monitoring, and AI-assisted development tools like GitHub Copilot to deliver high-quality solutions.
5–8 years of experience in software engineering with Azure-based solution development.
Strong proficiency in C#, .NET Core, ASP.NET Core, EF Core, Python, and JavaScript/TypeScript for frontend and APIs.
Hands-on experience with Azure cloud services including Azure App Service, Functions, AKS or Container Apps, Azure SQL/Cosmos DB, Azure Service Bus, and Azure DevOps or GitHub Actions.
Knowledge of Infrastructure as Code tools (Bicep and/or Terraform), containerization (Docker), Azure scripting (PowerShell, Azure CLI), and familiarity with Azure AI services including AI integration and GenAI concepts.
Experienced in designing scalable, secure, and maintainable cloud-native solutions on Microsoft Azure with strong pro-code engineering skills.
Comfortable integrating AI capabilities into applications using both .NET and Python SDKs, with practical exposure to Generative AI, agentic AI, and AI-assisted development tools.
Able to work collaboratively with technical architects and cross-functional distributed teams, emphasizing engineering excellence, automation, and continuous learning.