Senior Java Developer

Role:

We are seeking a highly skilled Senior Backend Java Developer with 5 or more years of hands-on experience in designing, developing, and maintaining robust backend systems. The ideal candidate will have strong expertise in Java, Spring, SQL, and unit testing frameworks such as JUnit or Mockito. Familiarity with AI-assisted development tools (like Claude Code, Cursor, GitHub Copilot) is essential. Experience with DevOps practices and cloud platforms like AWS is a plus.

Responsibilities:

• Design, build, and maintain scalable and secure backend services using Java and the Spring framework.
• Develop and execute unit and integration tests using JUnit, Mockito, or equivalent frameworks.
• Collaborate with frontend engineers, DevOps, and cross-functional teams to deliver complete and reliable features.
• Write and optimize SQL queries and manage relational databases to ensure high-performance data operations.
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  Leverage AI-assisted coding tools (e.g., Claude, Cursor, GitHub Copilot) to boost productivity and maintain code quality.
• Participate in code reviews, ensure adherence to best practices, and mentor junior developers as needed.
• Troubleshoot, diagnose, and resolve complex issues in production and staging environments.
• Contribute to technical documentation, architecture discussions, and Agile development processes (e.g., sprint planning, retrospectives).

Qualifications:

• Strong proficiency in Java and object-oriented programming concepts.
• Hands-on experience with Spring / Spring Boot for building RESTful APIs and backend services.

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  Proficiency in testing frameworks such as JUnit, Mockito, or equivalent.
• Solid experience in writing and optimizing SQL queries for relational databases (e.g., PostgreSQL, MySQL).
• Experience using AI-assisted coding tools (e.g., ClaudeCode, Cursor, GitHub Copilot) in a production environment.
• Experience in building features using LLM APIs, AI workflows, or chatbots, with the ability to explain the architecture and key technical challenges involved.
• Experience in deploying AI-integrated services on AWS, including the deployment approach and services used.
• Understanding of DevOps tools and practices (CI/CD, Docker, etc.)
• Experience with AWS services (e.g., EC2, RDS, S3, Lambda)
• Exposure to containerization and cloud-native development