Java AI Engineer

We are looking for an experienced Java AI Engineer with strong expertise in Java, Spring Boot, microservices, and Generative AI. The ideal candidate will develop scalable enterprise applications, integrate AI capabilities into software engineering workflows, and leverage LLMs, prompt engineering, and Retrieval-Augmented Generation (RAG) to improve application functionality, developer productivity, and software quality. Experience in secure application development and financial services environments will be advantageous.

Key Responsibilities :

- Design, develop, and maintain scalable Java applications and microservices using Java/J2EE and Spring Boot.

- Build and integrate Generative AI and LLM-powered capabilities into enterprise applications and engineering workflows.

- Implement prompt engineering, context assembly, and RAG-based solutions to improve the relevance and accuracy of AI-generated outputs.

- Integrate AI services and models with backend applications, databases, third-party platforms, and REST APIs.

- Develop and maintain web applications using Angular and integrate frontend components with Java-based backend services.

- Design secure and maintainable solutions using MVC architecture, modular design, dependency injection, and established software engineering principles.

- Implement secure APIs and authentication mechanisms using OAuth2, JWT, and appropriate access controls.

- Apply AI-assisted development tools to support coding, code reviews, test generation, debugging, and documentation.

- Validate AI-generated code and outputs for correctness, security, performance, maintainability, and compliance with engineering standards.

- Develop automated quality checks and testing frameworks for AI-enabled applications and conventional software components.

- Build and maintain CI/CD pipelines and support containerised application deployments using Docker and Kubernetes/OpenShift.

- Troubleshoot application issues, perform root cause analysis, and optimise system performance, reliability, and scalability.

- Collaborate with product managers, architects, QA, DevOps, and business teams to refine requirements, estimate work, and deliver solutions in Agile environments.

- Evaluate emerging AI technologies and engineering tools, develop prototypes, and recommend practical improvements based on business value.

- Follow secure development practices and address AI-specific risks, including prompt injection, data exposure, and unsafe model outputs.

Required Skills & Experience :

- 5 - 8 years of experience in Java development, backend engineering, or full-stack application development.

- Strong hands-on proficiency in Java/J2EE and Spring Boot.

- Experience designing and developing microservices, REST APIs, and scalable enterprise applications.

- Practical experience with Generative AI, LLM integration, and AI-assisted software development.

- Understanding of prompt engineering, context assembly, and RAG implementation.

- Experience integrating applications with databases, external services, and AI models through APIs.

- Good understanding of Angular and frontend-backend integration.

- Knowledge of software design patterns, MVC, modular architecture, and dependency injection.

- Experience with secure API development, OAuth2, JWT, and application security principles.

- Familiarity with Git, CI/CD pipelines, automated testing, and code quality practices.

- Exposure to Docker, Kubernetes, or OpenShift and cloud-based application deployment.

- Strong debugging, performance optimisation, problem-solving, and collaboration skills.