Senior Developer
Sonata Software1 day ago
Bengaluru, IndiaSenior
Responsibilities
- Modernize and refactor legacy Java applications and enterprise systems.
- Upgrade Java versions and modernize Spring and Spring Boot applications.
- Refactor monolithic applications toward microservices and cloud-native architectures while reducing technical debt.
- Analyze legacy codebases, dependencies, architecture, and business logic to plan modernization activities.
- Apply AI-assisted SDLC workflows across requirements, design, development, testing, review, and documentation.
- Use AI coding agents to analyze codebases, generate and refactor code, create tests, identify dependencies and dead code, and support documentation.
- Create specifications, implementation plans, prompts, context files, agent instructions, and coding guidelines for consistent AI-assisted development.
- Review and validate AI-generated code for correctness, performance, security, maintainability, and scalability.
- Develop and enhance unit, integration, and regression test suites and use AI to improve test coverage.
- Develop and modernize applications for AWS and other cloud-native deployment environments.
- Contribute to CI/CD pipelines and automated build and deployment processes.
- Collaborate with engineering, DevOps, architecture, product, and project teams and communicate modernization progress, risks, and dependencies.
- Share AI-SDLC practices, reusable prompt patterns, and lessons learned with the engineering team.
Requirements
- Hands-on experience as a Java Engineer modernizing enterprise Java applications and legacy systems.
- Practical experience using Claude Code, GitHub Copilot, Cursor, or similar agentic AI coding assistants in real project delivery.
- Strong experience with Java, Spring Boot, AI-assisted development, legacy modernization, microservices, REST APIs, AWS, JUnit, Mockito, CI/CD, and Git.
- Experience applying AI agents to understand, refactor, and modernize existing codebases.
- Strong prompt engineering and context engineering skills, including creating specifications, agent instructions, context files, and coding rules.
- Ability to validate AI-generated code rather than accepting AI output blindly.
- Understanding of AI risks including hallucinations, insecure code, licensing concerns, data privacy, and confidentiality.
- Ability to demonstrate real-world AI-SDLC implementation with measurable productivity, development-effort, test-coverage, or modernization improvements.
- Experience with AWS services such as EC2, ECS/EKS, Lambda, RDS, and S3 is beneficial.
- Experience with Docker, Kubernetes, Kafka, AWS SQS/SNS, or other messaging and event-streaming technologies is beneficial.
- Experience with OpenRewrite or similar Java migration tools, MCP, AI agent workflows, custom AI instructions, or AI-enabled CI/CD workflows is beneficial.
- Exposure to SonarQube, Snyk, Checkmarx, React, or Angular is beneficial.
- Experience in healthcare, life sciences, clinical trials, or regulated environments and knowledge of GxP, 21 CFR Part 11, HIPAA, or GDPR are advantageous.