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Java Backend Developer (AI & RAG)

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Description

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

Skills

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See also

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