Java Backend Developer - Microservices Architecture

Job Description :

Key Responsibilities :

Technical Design & Development :

- Own and lead end-to-end development of core features or services across backend and frontend components.

- Collaborate with architects and senior engineers to design scalable, reliable, and maintainable distributed systems.

- Write clean, modular, testable code following TDD, design patterns, SOLID principles, and industry best practices.

- Ensure smooth integration of backend services with frontend applications and third-party systems.

Mentorship & Technical Leadership :

- Promote engineering best practices including peer reviews, static code analysis, CI/CD hygiene, and code quality standards.

- Contribute to defining and improving coding guidelines, development workflows, and engineering processes.

Innovation & Tooling :

- Leverage Large Language Models (LLMs) and AI-assisted engineering tools to optimize development, debugging, and testing workflows.

- Identify and propose new tools, frameworks, or libraries that enhance team productivity and

software quality.

Quality & Performance :

- Develop and maintain automated test suites for unit, integration, functional, and end-to-end testing.

- Monitor production systems, analyze logs and performance metrics, and proactively address

performance bottlenecks.

Cross-Team Collaboration :

- Actively participate in sprint planning, estimation, retrospectives, and post-mortems.

- Contribute to design documentation, architecture specs, and internal knowledge bases.

Skills & Qualifications :

Must-Have Skills :

- Strong backend development expertise with Java / Spring Boot, and working exposure to frontend technologies (React/Angular is a plus).

- Deep knowledge of RESTful APIs, microservices architecture, and CI/CD pipelines.

- Strong proficiency in Data Structures & Algorithms (DSA) and system design fundamentals.

- Hands-on experience with AWS Cloud Services (Lambda, ECS/EKS, S3, RDS, CloudWatch, SNS/SQS, etc.).

- Strong skills in debugging, performance tuning, and distributed system troubleshooting.

- Experience with Kubernetes/Docker, Git, and Agile methodologies.

- Interest or experience in integrating LLMs / AI tools into engineering workflows for code

generation, testing, or automation.