Java Backend Developer (AI & RAG)

Job Summary We are seeking a highly skilled **Senior Java Developer** with strong expertise in **Java, Spring Boot, Microservices, Messaging Systems, Design Patterns, Multithreading, and Generative AI technologies**. The ideal candidate should have hands-on experience in building scalable enterprise applications and working with **RAG (Retrieval-Augmented Generation)** based AI solutions. Key Responsibilities - Design, develop, and maintain scalable backend applications using **Java and Spring Boot**. - Develop and consume **RESTful APIs and Microservices**. - Implement secure applications using **Spring Security/Spring Authentication**. - Work with messaging platforms such as **Kafka Or RabbitMQ** for event-driven architectures. - Develop batch processing solutions using **Spring Batch**. - Build and integrate **AI/GenAI solutions**, including **RAG-based applications**. - Implement efficient **multithreading and concurrency** solutions for high-performance applications. - Apply **Design Patterns** and software engineering best practices to deliver maintainable code. - Optimize application performance, scalability, and reliability. - Collaborate with architects, product teams, and stakeholders in designing enterprise solutions. - Participate in code reviews and mentor junior developers. Required Skills - Strong experience in **Java (Core Java 8/11/17+)** - Extensive experience with **Spring Boot** - Strong knowledge of: - Spring Security / Authentication & Authorization - Spring Batch - REST APIs & Microservices - Hands-on experience with: - Apache Kafka - RabbitMQ - Strong understanding of: - Object-Oriented Programming (OOP) - SOLID Principles - Design Patterns (Factory, Builder, Strategy, Observer, Singleton, etc.) - Expertise in: - Multithreading - Concurrency - Collections Framework - Exception Handling - Experience working with SQL databases. - Good understanding of CI/CD and Agile methodologies. AI/GenAI Requirements - Hands-on experience with **Generative AI** solutions. - Knowledge of **RAG (Retrieval-Augmented Generation)** frameworks and architectures. - Experience with: - LLM Integration - LangChain/LlamaIndex (preferred) - Vector Databases (Pinecone, ChromaDB, Weaviate, FAISS) - Prompt Engineering Preferred Skills - Cloud experience (AWS/Azure/GCP) - Docker & Kubernetes - Elasticsearch - Knowledge of AI-powered enterprise application development