Software Engineer

Hitachi Solutions; Pune District; On-site; INR 1,400,000 - 2,800,000; Full time

Job summary

Hitachi Solutions in India is seeking an Azure solution engineer to design and deliver scalable Azure-based solutions. You will work with Technical Architects and cross-functional teams to leverage AI, Copilot, and Azure AI Foundry for development acceleration.

You will design Azure solutions using C#, .NET Core, REST APIs, and frontend frameworks, while implementing cloud-native patterns and AI-enabled workflows. Strong focus on reliability and security is expected.

Qualifications

• 5–8 years of software engineering experience in Azure-based solution development.
• Strong proficiency with C#, .NET Core, ASP.NET Core, EF Core and Web APIs.
• Practical Python experience for Azure automation, integrations, or AI workloads.
• Solid understanding of cloud-native architectures (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.
• PowerShell and Azure CLI scripting.
• Monitoring/logging/telemetry in Azure.

Responsibilities

• Design and develop Azure-based solutions using C#, .NET Core, ASP.NET Core, EF Core, REST APIs and front-end frameworks (Angular/React).
• Develop supporting services and components using Python for AI integration, automation, and background processing.
• Build cloud-native apps using Azure App Service, Functions, Container Apps or AKS.
• Implement data solutions with Azure SQL, Cosmos DB, Blob/Table Storage; ensure scalability.
• Integrate solutions using Service Bus, Event Grid, Event Hubs for asynchronous messaging.
• Apply Well-Architected Framework across reliability, security, performance, cost, operations.
• Design and implement custom Azure services, APIs, microservices, and background workers (pro-code).
• Write automation scripts using Python, PowerShell, and Azure CLI for deployments and operations.
• Develop and maintain IaC using Bicep and/or Terraform.
• Integrate enterprise systems via REST APIs, SDKs, and Azure-native services.
• Apply modern architectural patterns: microservices, event-driven, serverless, containers.
• Ensure code quality, maintainability, and extensibility through best practices.
• Implement and maintain CI/CD pipelines using Azure DevOps or GitHub Actions.
• Apply containerization with Docker and manage multi-environment deployments.
• Use configuration-as-code to standardize environments.
• Implement monitoring, logging and observability with Application Insights, Log Analytics, OpenTelemetry.
• Write unit, integration and component tests to ensure quality.

Skills

C#

NET Core

ASP.NET Core

EF Core

REST APIs

Angular

React

Python

Azure DevOps

GitHub Actions

IaC

Bicep

Terraform

Docker

AKS

Azure Functions

App Service

Cosmos DB

Azure SQL

Service Bus

Event Grid

Event Hubs

Entra ID

Azure CLI

PowerShell

OpenTelemetry

Application Insights

GenAI

Tools

GitHub Actions

Azure DevOps

Docker

Job description

Job Description

Overview

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

• 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.
• 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.
• 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.
• 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

• 5–8 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.
• 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.