Sr. Java Developer with GenAI Integration

As a skilled Senior Java Backend Engineer, you will be joining a team that focuses on building scalable and high-performance backend systems for Generative AI applications. Your key responsibilities will include designing APIs, orchestrating AI agents, and integrating Large Language Models (LLMs) into production-ready systems. This role is perfect for backend developers who have a passion for modern AI technologies and distributed systems. - Design, build, and maintain scalable backend services using Java and the Spring Boot framework - Develop APIs to enable LLM integration and support AI agent orchestration workflows - Architect microservices to power RAG (Retrieval-Augmented Generation) and other LLM-driven systems - Optimize performance through efficient caching strategies and vector database interactions - Integrate and manage connections with multiple LLM providers (e.g., OpenAI, Gemini, Claude), including rate limiting and failover handling - Implement real-time streaming features for conversational AI systems using WebSockets or similar technologies - Ensure robust system observability with logging, monitoring, and tracing To qualify for this position, you should have: - At least 3 years of hands-on experience with Java and Spring Boot for backend development - Strong grasp of RESTful API design principles and microservices architecture - Proficiency with core Spring modules like Spring Security, Spring Data JPA, and Spring Cloud - Experience working with relational and NoSQL databases such as PostgreSQL, MongoDB, and Redis - Familiarity with message brokers like RabbitMQ or Apache Kafka - Expertise in caching mechanisms and system performance tuning In addition, you should have experience in: - Integrating LLM APIs (OpenAI, Gemini, Claude, etc.) into backend services - Working with vector databases and semantic search technologies - Using AI agent orchestration frameworks such as LangGraph - Implementing RAG systems effectively - Developing streaming responses using WebSockets or server-sent events - Knowledge of prompt templating and management systems Nice to have skills include: - Experience in fine-tuning LLMs and managing model deployment pipelines - Knowledge of self-hosted LLM environments and infrastructure management - Exposure to observability tools like LangSmith or custom monitoring setups - Familiarity with natural language to SQL systems or BI applications powered by LLMs If you meet the qualifications and are interested in the role, please consider filling out your details in the enclosed form provided in the job description.,