AI/GenAI/ML (Java Backend)

Job Description: We are looking for an experienced Java Developer with AI/GenAI expertise to design, develop, and integrate scalable enterprise applications with modern AI capabilities. The ideal candidate will have strong hands-on experience in Java/Spring Boot and practical knowledge of Generative AI, LLMs, APIs, and AI-powered application development.

Key Responsibilities: Design, develop, test, and maintain scalable applications using Java, Spring Boot, and REST APIs. Build microservices and integrate them with enterprise applications and cloud platforms. Develop and integrate Generative AI/LLM capabilities into Java applications. Work with LLM APIs such as OpenAI, Azure OpenAI, or other enterprise AI platforms. Develop AI-powered features such as chatbots, document processing, summarization, classification, and intelligent search. Implement RAG (Retrieval-Augmented Generation) solutions using vector databases. Work with embeddings, prompt engineering, AI agents, and LLM orchestration frameworks. Integrate AI services securely through REST APIs and SDKs. Develop backend services for AI/ML applications and optimize performance and scalability. Collaborate with product managers, architects, data scientists, and frontend developers. Write clean, maintainable, well-tested code and participate in code reviews. Troubleshoot production issues and continuously improve application reliability.

Required Skills: Strong proficiency in Java 8/11/17+.Strong experience with Spring Boot, Spring Framework, REST APIs, and Microservices. Experience with Hibernate/JPA and SQL databases. Knowledge of design patterns, OOP, data structures, and multithreading. Experience with Git and CI/CD pipelines. AI / GenAIHands-on experience with Generative AI and Large Language Models (LLMs).Experience integrating LLM APIs such as OpenAI/Azure OpenAI, Anthropic, or Google Gemini. Knowledge of Prompt Engineering, Embeddings, Vector Databases, and RAG.Experience with vector databases such as Pinecone, FAISS, Weaviate, or Milvus is a plus. Familiarity with AI frameworks such as LangChain, LangGraph, Spring AI, or LlamaIndex. Understanding of AI agents, tool/function calling, and evaluation/monitoring is desirable. Basic understanding of Python and AI/ML concepts is an advantage. Experience with AWS, Azure, or GCP.Knowledge of Docker and Kubernetes. Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps. Understanding of cloud-native architecture and security best practices.

Preferred Qualifications: Experience building enterprise-grade AI-powered applications. Knowledge of MCP, AI agents, function calling, and LLM observability. Experience with Kafka or other messaging systems. Knowledge of NoSQL databases such as MongoDB or Redis. Strong problem-solving and communication skills.