Senior Developer

Sonata Software; Bengaluru; On-site; INR 900,000 - 1,400,000; Full time

Job summary

Sonata Software in Bengaluru seeks a Java Engineer to lead AI‑SDLC driven modernization of enterprise Java apps. You will modernize legacy systems, upgrade Java/Spring, and move toward microservices and cloud‑native architectures.

You’ll apply AI tools for requirements, design, development, testing, and documentation, ensuring quality and security throughout. Ideal candidates have hands‑on AI coding tool experience (Claude Code, Copilot, Cursor), strong prompt engineering, and a track record

Qualifications

• Hands‑on experience with AI‑SDLC and AI coding assistants in real projects.
• Proven ability to apply AI tools (Claude Code, Copilot, Cursor) to modernization work.
• Strong prompt engineering and context engineering skills.
• Experience creating specifications, agent instructions, context files, and coding rules for AI‑assisted development.
• Ability to validate AI‑generated code and manage AI‑related risks (hallucinations, security, licensing).

Responsibilities

• Modernize and refactor legacy Java applications and enterprise systems.
• Upgrade Java versions and Spring/Spring Boot, moving toward microservices.
• Apply AI‑SDLC workflows across requirements, design, development, testing, and documentation.
• Collaborate with architects and teams to ensure quality, security, and scalability.
• Lead AI‑assisted code reviews and optimize test coverage with AI tools.

Skills

Java

Spring Boot

AI-SDLC

AI-Assisted Development

Claude Code

GitHub Copilot

Cursor

Generative AI

AI Coding Agents

Spec-Driven Development

Legacy Modernization

Java Modernization

Microservices

REST APIs

AWS

JUnit

Mockito

CI/CD

Git

Tools

Docker

Kubernetes

OpenRewrite

MCP

AI agent workflows

Job description

Job Title- Java Engineer (AI-SDLC Modernization)

Location- Bangalore / Hyderabad / Chennai

Roles and Responsibilities

We are looking for experienced Java Engineers with strong expertise in Java application modernization and AI-driven Software Development Lifecycle (AI-SDLC) practices.

The ideal candidate will have hands‑on experience modernizing enterprise Java applications using AI coding agents and assistants across requirements, design, development, testing, code review, and documentation.

The role focuses on legacy application modernization , including Java and Spring upgrades, refactoring monolithic applications, improving test coverage, and transitioning applications toward microservices and cloud-native architectures.

Candidates must have practical experience using AI development tools such as Claude Code, GitHub Copilot, Cursor, or similar agentic AI coding assistants in real project delivery—not just basic code autocomplete.

Key Responsibilities

Java Application Modernization

• Modernize and refactor legacy Java applications and enterprise systems.
• Upgrade Java versions, preferably from Java 8/11 to Java 17/21 .
• Upgrade and modernize Spring/Spring Boot applications.
• Refactor monolithic applications and progressively move toward microservices and cloud-native architectures .
• Identify and reduce technical debt while maintaining application functionality and stability.
• Analyze existing codebases, dependencies, architecture, and legacy business logic.

AI‑SDLC & AI‑Assisted Development

• Apply AI-driven SDLC workflows across requirements, design, development, testing, review, and documentation.
• Convert requirements into clear specifications and implementation plans using AI-assisted workflows.
• Use AI coding agents to analyze codebases, generate and refactor code, create automated tests, and support documentation.
• Develop effective prompts, specifications, context files, agent instructions, and coding guidelines to achieve consistent AI‑assisted development outcomes.
• Use AI agents to identify dependencies, understand legacy code, detect potential dead code, and plan modernization activities.
• Apply an AI‑SDLC workflow such as:

Specification → Planning → AI‑Assisted Development → AI‑Assisted Testing → Human Review → Validation → Merge

Code Quality & Testing

• Review and validate all AI‑generated code before implementation or merge .
• Ensure AI‑generated code meets standards for correctness, performance, security, maintainability, and scalability .
• Develop and enhance unit, integration, and regression test suites.
• Use AI to improve test coverage while ensuring that generated tests accurately validate existing behavior.
• Identify and correct errors, hallucinations, security vulnerabilities, or inappropriate recommendations generated by AI tools.

Cloud & DevOps

• Develop and modernize applications for cloud-native environments.
• Work with AWS services and cloud deployment architectures.
• Contribute to CI/CD pipelines and automated build and deployment processes.
• Collaborate with DevOps and engineering teams to improve application delivery and operational efficiency.

Collaboration & Delivery

• Work closely with architects, developers, product managers, and project leads.
• Participate in Agile ceremonies including stand‑ups, sprint planning, reviews, and retrospectives.
• Communicate technical decisions, modernization progress, risks, and dependencies effectively.
• Share AI‑SDLC practices, prompt patterns, reusable approaches, and lessons learned with the wider engineering team.

AI‑SDLC – Mandatory

• Hands‑on, regular experience using AI coding tools such as:
• Claude Code
• GitHub Copilot
• Cursor
• Similar AI/agentic coding assistants
• Practical understanding of AI‑assisted software development and AI‑SDLC workflows .
• Experience using AI agents to analyze, understand, refactor, and modernize existing codebases.
• Strong prompt engineering and context engineering skills.
• Experience creating specifications, agent instructions, context files, and coding rules for AI‑assisted development.
• Ability to validate and review AI‑generated code rather than blindly accepting AI output.
• Understanding of AI‑related risks including hallucinations, insecure code, licensing concerns, data privacy, and confidentiality .
• Ability to demonstrate real‑world examples of AI‑SDLC implementation, including measurable improvements such as productivity gains, reduced development effort, improved test coverage, or faster modernization.

Mandatory Skills : Java | Spring Boot | AI‑SDLC | AI‑Assisted Development | Claude Code | GitHub Copilot | Cursor | Generative AI | AI Coding Agents | Spec‑Driven Development | Legacy Modernization | Java Modernization | Microservices | REST APIs | AWS | JUnit | Mockito | CI/CD | Git

Good‑to‑Have Skills:

AWS: EC2, ECS/EKS, Lambda, RDS, S3. , Docker and Kubernetes. Kafka, AWS SQS/SNS, or other messaging/event-streaming technologies. OpenRewrite or similar automated Java migration tools. MCP (Model Context Protocol) and AI agent workflows. Custom AI agent instructions and AI-enabled CI/CD workflows. SonarQube, Snyk , Checkmarx , or similar code quality/security tools. React or Angular exposure. Experience in healthcare, life sciences, clinical trials, or regulated environments. Knowledge of GxP , 21 CFR Part 11, HIPAA, or GDPR is an advantage.

A BOUT SONATA SOFTWARE

Sonata Software is an AI‑first modernization engineering company that helps enterprises transform legacy systems into intelligent, scalable business platforms. Powered by its Platformation ™ framework and Harmoni.AI platform, Sonata delivers AI‑led modernization across cloud, data, AI, Dynamics, test automation, and managed services. Headquartered in Bengaluru, India, Sonata has more than $1.2 billion in revenue and 6,400+ AI engineers supporting global delivery across regions including the US, UK, India, Malaysia, Mexico, Australia, DACH, and the Nordics. With deep partnerships across Microsoft, AWS, Salesforce, and Snowflake, Sonata helps Fortune 500 enterprises accelerate innovation, improve efficiency, and drive sustainable growth.

For more information, please visit www.sonata-software.com