The Child Support System Enhancement Effort aims to transform existing functionality from a legacy mainframe system into an enhanced, web-based platform. This transformation is a continuation of the current enhancement effort and will improve user experience by integrating with the existing web-based application in an Agile development environment.
The Lead Full Stack Java Developer will lead the enhancement effort to build a user-friendly web-based platform. This role requires expertise in full-stack development, architecture design, and Agile collaboration. The Lead Developer will focus on improving efficiency and leveraging AI-powered development practices to deliver high-quality solutions.
The Lead Full Stack Java Developer will design and develop robust backend services using Java(8+ or higher), Spring Boot, and Spring Data JPA/Hibernate, alongside building responsive front-end interfaces with JavaScript, HTML5, CSS, and Bootstrap. Responsibilities include creating RESTful APIs, integrating external systems via SOAP/REST web services and messaging platforms, and using AI tools to accelerate development—including code generation, code transformation, automated unit test creation, security vulnerability detection, and intelligent suggestions within IDEs. Additional duties include conducting unit and automated testing, supporting data migration to relational databases (DB2, PostgreSQL, Oracle), and contributing to CI/CD pipeline development.
The Lead Full Stack Java Developer will have strong experience in Java full-stack development, Spring Framework, and RESTful API design, combined with front-end proficiency in JavaScript, HTML5, CSS, and Bootstrap. Expertise in relational databases, writing SQL queries and stored procedures, and familiarity with testing frameworks (JUnit, Mockito, Selenium) is essential. Knowledge of DevOps practices including Git-based version control, CI/CD pipelines (Jenkins, GitHub Actions), and build tools(Maven/Gradle) is required. Secure coding practices and strong problem-solving, communication, and collaboration skills are critical for success.
Experience with agentic AI integration in the development lifecycle—such as code generation, code transformation (COBOL to Java), test script generation, unit testing, security scanning, and use of AI-assisted IDE is highly desired. Additional expertise in applying agentic AI for tasks like intelligent code refactoring, and automated documentation will be a strong advantage.
Familiarity with message queues (JMS, RabbitMQ, Kafka), data migration strategies, and performance tuning will be a strong plus.
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