Java AI developer

We’re looking for a talented AI developer to build scalable, production-ready Spring Boot microservices. You’ll design and implement high-performance web services, develop intelligent tool-using agents, and work confidently with cloud-native architectures and databases. You’ll own the development lifecycle, including design, implementation, testing, and optimization.

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• Experience in the programming languages Java and JavaScript \n

• Decent understanding of the software development life cycle \n

• Basic programming skills using object-oriented programming (OOP) languages with in-depth knowledge of common APIs and data structures like Collections, Maps, lists, Sets, etc. \n

• Knowledge of relational databases (e.g., MySQL, PostgreSQL), basic SQL query language skills \n, * Master’s Degree in Computer Science (CS) \n

• 0-1 year of practical experience in Java coding \n

• Experience using Spring, Maven, React.js, HTML, CSS \n

• Knowledge of other contemporary Java technologies (e.g., Weblogic, RabbitMQ, Tomcat, etc.)

• Develop scalable web applications using Java 8/17, Spring Boot, SQL, NoSQL, Kafka, RabbitMQ, Angular 2+, React.js, HTML5, CSS, JavaScript, and TypeScript. \n

• Write clean and efficient code, and ensure code maintainability and reusability. \n

• Conduct Testing to ensure application and reliability. \n

• Perform code reviews to ensure code quality, consistency, and adherence to best practices. \n

• Participate in Agile Scrum team and own the full development lifecycle, including project planning, design, implementation, testing, and optimization. \n

• Create and maintain comprehensive technical documentation for applications, APIs, and deployment procedures. \n

• Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices. \n

• Stay up to date with the latest technologies for Java development. \n

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AI Integration

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• Implement RAG pipelines using Spring AI and LangChain4j with vector database integration. \n

• Stay up to date with the latest RAG technologies and best practices, including chunking strategies, embeddings, retrieval optimization, and reranking techniques \n

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