Senior AI Full Stack Java Developer

Key Responsibilities

• Design, develop, and maintain enterprise-grade full-stack applications using Java/J2EE, Spring Boot, Angular, and Microservices.
• Drive AI-assisted software engineering by leveraging Generative AI tools to improve development productivity, quality, and compliance.
• Build secure, scalable, and maintainable applications following MVC architecture, modular design, and dependency injection principles.
• Develop and integrate REST APIs, third-party services, databases, and authentication mechanisms using OAuth2 and JWT.
• Apply advanced AI engineering concepts, including Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI quality/compliance controls.
• Collaborate with Agile teams for solution design, estimation, technical discussions, and requirement refinement.
• Perform code reviews, troubleshoot production issues, optimize application performance, and support incident resolution.
• Implement DevSecOps best practices, CI/CD pipelines, automated testing, containerization, and Kubernetes/OpenShift deployments.
• Evaluate emerging technologies and recommend innovative solutions to improve engineering capabilities.
• Ensure adherence to security, regulatory compliance, AI governance, ethical AI practices, and cyber risk management.

Required Skills

• Strong experience in Java/J2EE, Spring Boot, and Angular.
• Expertise in Microservices architecture and REST API development.
• Experience with Java EE technologies such as JDBC, JTA, JCA, JNDI, JAF, and JavaMail.
• Hands-on experience with Generative AI, Prompt Engineering, and RAG frameworks.
• Knowledge of OAuth2, JWT, secure coding practices, and API security.
• Experience with CI/CD pipelines, Git, Jenkins, Docker, Kubernetes, and OpenShift.
• Good understanding of DevSecOps practices, automation, and cloud-native application development.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication and stakeholder management abilities.

Preferred Skills

• Experience in Financial Services or Banking domain.
• Exposure to AI governance, LLM security, ethical AI, and regulatory compliance.
• Experience with performance tuning, code quality tools, and engineering best practices.
• Familiarity with SAS Enterprise Miner or related AI/analytics platforms is an added advantage.