Senior Java Backend Engineer – AI-Augmented Engineering

Senior Java Backend Engineer to build scalable, production-grade enterprise applications for a large-scale digital transformation program. This role is strongly focused on Java, Spring Boot, microservices, and cloud-native development, with AI-powered engineering tools integrated into the software development lifecycle. You'll work as a hands-on builder, using tools such as GitHub Copilot, Cursor, Claude Code, and OpenAI Codex to accelerate development, testing, debugging, refactoring, and technical documentation while maintaining high engineering standards.
Your Impact
Design, develop, and maintain scalable backend applications using Java, Spring Boot, and microservices architecture.
Build robust RESTful APIs and backend services supporting enterprise operational workflows.
Develop cloud-native solutions using AWS, Kubernetes, Docker, and CI/CD pipelines.
Integrate backend services with enterprise platforms through MuleSoft, Kinesis, messaging systems, and third-party APIs.
Use AI-powered development tools throughout the SDLC to accelerate coding, debugging, testing, refactoring, code reviews, and technical documentation.
Apply AI tools thoughtfully to improve engineering productivity while validating generated code for quality, security, performance, and maintainability.
Collaborate with Product Owners, architects, and business stakeholders to translate requirements into scalable technical solutions.
Optimize applications for performance, security, scalability, and reliability.
Develop and maintain unit, integration, and automated tests to support high-quality releases.
Participate in technical design discussions, code reviews, and continuous improvement initiatives.
Troubleshoot production issues and contribute to application modernization and digital transformation initiatives.
Skills & Experience
Must Have
7+ years of hands-on experience in Java backend development.
Strong expertise in Java, Spring Boot, REST APIs, and microservices.
Experience developing and supporting enterprise-scale backend applications.
Hands-on experience with AWS, Docker, Kubernetes, and CI/CD pipelines.
Experience integrating applications with APIs, messaging platforms, or enterprise integration technologies.
Practical experience using AI-powered software development tools, such as GitHub Copilot, Cursor, Claude Code, or OpenAI Codex.
Ability to demonstrate how AI tools have been used for code generation, debugging, test creation, refactoring, code reviews, documentation, or developer productivity.
Strong understanding of software engineering best practices, testing, security, performance, and scalability.
Strong troubleshooting and problem-solving skills.
Excellent written and verbal communication and collaboration skills.
Set Yourself Apart With
Experience with MuleSoft, Amazon Kinesis, Kafka, or other messaging/event-driven platforms.
Experience integrating with complex enterprise or third-party vendor systems.
Experience using AI agents or LLM-powered tools beyond basic code completion.
Exposure to AI-assisted application modernization or large-scale engineering transformation.
Experience with cloud-native architecture and distributed systems.
Experience supporting production systems in high-volume or mission-critical environments.

Work arrangement
Yes