Senior Software Engineer

Introduction

Welcome to Gallagher in India — where expertise, technology, and purpose come together. Since 2006, Gallagher in India has supported global teams by delivering quality, service, and speed through deep expertise, smart technology, and specialized knowledge services. More than just an operations center, it’s a place where careers grow through collaboration, continuous learning, and purposeful work. We drive efficiency, compliance, and innovation so our teams can focus on serving clients. If you enjoy solving problems and working with purpose, Gallagher is the place where you can grow and feel a sense of belonging.

Overview

Senior Software Engineer – Java Technologies & AI-Enabled SDLC

Role Summary

We are seeking an experienced Senior Software Engineer specializing in Java technologies to design, develop, test, and deliver scalable, secure, and reliable enterprise applications.

The ideal candidate will have strong hands-on expertise in Java, Spring Boot, REST APIs, microservices, cloud-native development, DevOps, and automated testing, with demonstrated ability to leverage AI and Generative AI technologies across the Software Development Life Cycle (SDLC) to improve engineering productivity, code quality, testing efficiency, and speed to market.

This is a hands-on engineering role requiring strong technical ownership, problem-solving capabilities, collaboration, and a continuous-improvement mindset.

Key Responsibilities

Java Engineering & Application Development

Design, develop, enhance, and maintain enterprise applications using Java and Java/Jakarta EE technologies.

Develop scalable services and APIs using Spring, Spring Boot, REST APIs, and microservices architecture.

Write clean, maintainable, reusable, and well-tested code following established engineering standards and design principles.

Participate in solution design, technical design reviews, code reviews, and architecture discussions.

Troubleshoot complex application, integration, performance, and production issues.

Develop unit and integration tests and ensure adequate automated test coverage.

Support application modernization, technical-debt reduction, and continuous improvement initiatives.

Work closely with Product Owners, Business Analysts, QA, architects, DevOps engineers, and production support teams throughout the SDLC.

AI-Enabled SDLC

Actively use AI-assisted software engineering tools and Generative AI capabilities to accelerate development activities across the SDLC.

Apply AI to improve requirements understanding, solution design, code generation, code refactoring, unit-test creation, test-data generation, defect analysis, documentation, and troubleshooting.

Effectively use enterprise-approved AI coding assistants, such as GitHub Copilot, where available.

Evaluate AI-generated code for correctness, security, maintainability, performance, and alignment with enterprise engineering standards rather than accepting generated code without validation.

Identify repetitive engineering activities that can be automated or accelerated through AI agents, reusable prompts, workflows, or engineering accelerators.

Contribute reusable AI-enabled engineering assets, patterns, and best practices that can be adopted by other development teams.

Measure and demonstrate improvements achieved through AI adoption, including engineering productivity, development cycle time, quality, automation, and reduction of repetitive manual effort.

Ensure AI-assisted development complies with applicable organizational standards for security, privacy, intellectual property, data protection, and responsible AI usage.

How you'll make an impact

Required Technical Skills

Strong hands-on experience with Java, with solid understanding of object-oriented programming, data structures, design patterns, concurrency, exception handling, and performance optimization.

Strong experience with Spring Framework and Spring Boot.

Experience designing and developing RESTful APIs and microservices.

Experience with persistence technologies such as JPA/Hibernate and relational databases.

Strong understanding of SQL and database design concepts.

Experience with build and dependency-management tools such as Maven or Gradle.

Experience with automated unit and integration testing using technologies such as JUnit, Mockito, REST Assured, or equivalent frameworks.

Experience with source-control and CI/CD practices using technologies such as Git and Jenkins, GitHub Actions, Azure DevOps, or equivalent platforms.

Understanding of containerized application development using Docker and exposure to Kubernetes or similar orchestration platforms.

Experience developing or supporting applications deployed to a major cloud platform such as Microsoft Azure, AWS, or Google Cloud Platform.

Strong knowledge of secure coding, application security, logging, monitoring, exception management, and production-support practices.

AI & GenAI Skills

Practical experience using Generative AI or AI coding assistants within software engineering activities.

Ability to create effective prompts and provide sufficient technical context to AI tools for software-development use cases.

Experience using AI for code generation, refactoring, unit-test generation, documentation, debugging, code explanation, and engineering productivity.

Understanding of the limitations and risks of AI-generated code and the importance of human review and validation.

Familiarity with LLMs, prompt engineering, AI agents, Retrieval-Augmented Generation (RAG), APIs, and enterprise AI integration patterns is preferred.

Exposure to technologies such as GitHub Copilot, Microsoft Copilot, Azure OpenAI, or comparable enterprise GenAI platforms is preferred.

Engineering & SDLC Expectations

The Senior Software Engineer will be expected to take ownership across the engineering lifecycle

Requirements Design Development Code Review Unit Testing Integration Testing Deployment Production Support C