Software Engineer

Azure Solution Engineer Overview The Azure Solution Engineer is responsible for designing, building, testing, deploying, and supporting end-to-end solutions on the Microsoft Azure platform. This role goes beyond traditional .NET full‑stack development and focuses on building AI-first, cloud-enabled, and automation-driven solutions using a mix of Pro-code (C#, Python, JavaScript/TypeScript and Azure scripting), DevOps, and Azure AI capabilities across the Azure ecosystem . The engineer will work closely with the Technical Architect and cross-functional teams to deliver scalable, secure, and maintainable Azure solutions. The role requires a strong foundation in Azure solution engineering and the ability to leverage AI, Generative AI, Copilot, and Azure AI Foundry as development accelerators. Key Responsibilities Core Azure Solution Development Design and develop Azure-based solutions using C#, .NET Core, ASP.NET Core, EF Core, REST APIs , and modern front-end frameworks ( Angular / React ) where applicable. Develop supporting services, tools, and components using Python where it is a natural fit in the Azure ecosystem (e.g., AI integration, automation, background processing). Build cloud-native applications using Azure App Service, Azure Functions, Azure Container Apps, and/or AKS , based on solution needs. Implement data solutions using Azure SQL, Cosmos DB, Blob Storage, and Table Storage , with attention to scalability and performance. Integrate solutions using Azure Service Bus, Event Grid, and Event Hubs for asynchronous and event-driven architectures. Apply Azure Well-Architected Framework principles covering reliability, security, performance, cost, and operational excellence. Pro-Code Engineering & Azure Integrations Design and implement custom Azure services, APIs, microservices, and background workers using pro-code approaches. Write automation and integration scripts using Python, PowerShell, and Azure CLI for environment setup, deployments, and operational tasks. Develop and maintain Infrastructure as Code using Bicep and/or Terraform . Integrate enterprise systems using REST APIs, external SaaS APIs, SDKs, and Azure-native integration services. Apply appropriate architectural patterns such as microservices, event-driven, serverless, and container-based architectures , based on solution requirements. Ensure code quality, maintainability, and extensibility through engineering best practices. DevOps & Engineering Excellence Implement and maintain CI/CD pipelines using Azure DevOps or GitHub Actions . Apply containerization using Docker and manage deployments across environments. Use scripting and configuration-as-code approaches to standardize environments and reduce manual effort. Implement monitoring, logging, and observability using Application Insights, Log Analytics , OpenTelemetry , and structured logging. Write unit tests, integration tests, and component tests to ensure solution quality and reliability. AI Solution Development Build AI-enabled solutions using Azure AI Services, Azure OpenAI, and Azure AI Foundry capabilities. Implement GenAI use cases such as Copilot , chat-based assistants, document processing, summarization, and knowledge search. Use Python and .NET SDKs to integrate AI models and services into applications. Understand and apply prompt engineering, embeddings, vector search, and RAG patterns at a foundational level. Contribute to Agentic AI solutions, orchestrating workflows using tools, APIs, and AI models. Apply Responsible AI , security, and data privacy principles in AI solutions. AI‑Assisted Development Use GitHub Copilot , Azure Copilot , and AI-assisted tools to improve developer productivity and code quality. Leverage AI for code generation, refactoring, test creation, documentation , scripting, and troubleshooting. Continuously evaluate emerging AI capabilities and adopt them pragmatically within delivery teams. Required Skills & Experience 4 years of experience in software engineering and Azure-based solution development. Strong proficiency in C#, .NET Core, and ASP.NET Core, EF Core, Web APIs Practical experience with Python for Azure automation, integrations, or AI-enabled workloads. Experience with JavaScript / TypeScript for frontend development and API integrations. Solid understanding of cloud-native architecture patterns (microservices, event-driven, serverless). Experience with Azure App Service, Azure Functions, AKS or Container Apps. Strong knowledge of Azure SQL and/or Cosmos DB. Experience with Azure Service Bus and asynchronous messaging patterns. Understanding of Entra ID (Azure AD), Managed Identities, and secure access patterns. Hands-on experience with Azure DevOps or GitHub Actions. • Working knowledge of IaC (Bicep and/or Terraform). • Experience with Docker and container-based deployments. • Experience with PowerShell and Azure CLI scripting. • Familiarity with monitoring, logging, and telemetry in Azure. Awareness and practical exposure to Azure AI Services / Azure OpenAI. Understanding of GenAI concepts (LLMs, prompts, embeddings, RAG). Ability to integrate AI capabilities into applications using .NET and Python SDKs. Willingness and curiosity to learn agentic AI and AI orchestration patterns. Experience using Copilot or similar AI tools in day-to-day development Strong problem-solving and analytical skills. Strong pro-code engineering mindset with attention to quality and scalability. Good communication skills with consulting mindset and ability to collaborate in distributed teams. Mindset of continuous learning and engineering excellence. Beware of scams Our recruiting team may communicate with candidates via our @hitachisolutions.com domain email address and/or via our SmartRecruiters (Applicant Tracking System) notification@smartrecruiters.com domain email address regarding your application and interview requests. All offers will originate from our @hitachisolutions.com domain email address. If you receive an offer or information from someone purporting to be an employee of Hitachi Solutions from any other domain, it may not be legitimate.