AI Engineer- Java

We are seeking a Software AI Engineer with strong backend development experience in Java combined with hands-on experience in AI/ML model development, to build and maintain scalable enterprise applications. The role spans backend services, API implementation, database integration, cloud deployment, and AI solutions—including RAG (Retrieval-Augmented Generation) architectures—under senior technical guidance We are seeking a Software Engineer with 3-5 years of solid backend development experience in Java to build and maintain scalable enterprise applications. The role focuses on hands-on development, API implementation, database integration, and supporting cloud-based deployments under senior technical guidance. In this role you will… Develop and maintain backend services using Java (Spring Boot). Build RESTful APIs following defined architectural standards; integrate with relational databases. Implement business logic, authentication mechanisms (JWT-based security), and microservices-based applications. Design, develop, and deploy AI/ML models (NLP, predictive analytics, computer vision). Implement Retrieval-Augmented Generation (RAG) architectures to enhance AI solutions with knowledge retrieval. Prepare data pipelines for training, preprocessing, and feature engineering. Containerize applications using Docker and support CI/CD pipelines and cloud deployments (AWS preferred). Write clean, testable, and maintainable code; implement unit and integration tests (JUnit, Pytest). Collaborate with cross-functional teams to integrate AI/ML solutions into production-ready applications. Monitor and optimize model and application performance; troubleshoot and resolve technical issues. Participate in code reviews, agile ceremonies, and knowledge-sharing initiatives. You have what it takes if you have… Technical Requirements Programming Proficiency in Java 17+ Java: Spring Boot (REST APIs, configuration), Spring Data JPA, Spring Security basics AL/ML Knowledge of machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Experience in RAG architectures, model training, evaluation, optimization, and deployment Familiarity with large language models (LLMs) is a plus Architecture APIs REST API development Basic understanding of microservices concepts Familiarity with OpenAPI/Swagger Database Experience with PostgreSQL/MySQL Writing queries and understanding relationships Exposure to migration tools (e.g., Alembic preferred) Cloud DevOps Docker (basic containerization) Exposure to AWS services (EKS, RDS preferred) Familiarity with CI/CD pipelines (GitHub Actions or similar) Basic logging and monitoring understanding #LI-Onsite