Senior .NET Azure Cloud Architect

We are looking for an experienced .NET/Azure Architect with strong hands-on expertise in building and modernizing cloud-native applications. The candidate should have solid experience in CI/CD automation and Infrastructure as Code using Terraform, along with practical exposure to modern AI-assisted software engineering, including building basic AI agents and awareness of concepts such as SDD and MCP. The candidate should be comfortable working across application development, cloud engineering, DevOps, and AI-enabled development practices. .NET & Application Engineering:

• Design, develop, and maintain scalable applications using C#, .NET / .NET Core, and ASP.NET Core.
• Develop and integrate REST APIs and microservices.
• Apply engineering practices such as SOLID principles, dependency injection, design patterns, and clean architecture.
• Design solutions for scalability, performance, resilience, and maintainability.
• Participate in technical design, code reviews, troubleshooting, and production issue resolution.

Microsoft Azure:

• Demonstrate strong hands-on experience with Azure services such as Azure App Service, Azure Functions, Azure API Management (APIM), Azure Service Bus / Event Hubs, Azure SQL, Azure Storage, Azure Key Vault, and Azure Monitor / Application Insights.
• Exposure to AKS / containerized applications is desirable.

CI/CD & DevOps:

• Demonstrate strong practical knowledge of Azure DevOps CI/CD pipelines.
• Experience creating and maintaining YAML-based build and deployment pipelines.
• Automate application build, testing, and deployments across environments.
• Possess a good understanding of branching strategies, release management, deployment approvals, and environment configuration.
• Exposure to GitHub Actions is an advantage.

Terraform / Infrastructure as Code:

• Hands-on experience with Terraform for provisioning and managing Azure infrastructure.
• Ability to create, understand, and modify Terraform modules.
• Understanding of Terraform state management, environments, variables, and reusable modules.
• Integrate Terraform provisioning with CI/CD pipelines.
• Understanding of secure handling of configuration and secrets.

AI / GenAI Fundamentals: The candidate does not need to be an AI/ML specialist, but should be comfortable adopting AI within software engineering.

• Understanding of Generative AI and LLM fundamentals.
• Ability to create simple AI agents / agentic workflows.
• Basic understanding of prompting and tool-based AI interactions.
• Awareness of RAG (Retrieval-Augmented Generation) concepts.
• Awareness of MCP (Model Context Protocol) and its purpose in connecting AI applications/agents with tools and contextual information.
• Awareness of SDD (Spec-Driven Development) and AI-assisted software development practices.
• Exposure to AI coding assistants such as GitHub Copilot or similar tools.
• Ability to identify practical opportunities where AI can improve development, testing, documentation, and engineering productivity.
• Exposure to Azure AI / Azure OpenAI / Microsoft Foundry is desirable, not mandatory.