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This role is ideal for engineers who have a strong foundation in Java-based backend development and are excited about integrating Generative AI, LLMs, and AI-driven solutions into enterprise-grade applications.\n\nResponsibilities: \nDesign, develop, and maintain scalable backend applications using Java and modern frameworks.\nLead the architecture and implementation of AI-powered features and services.\nBuild and integrate solutions leveraging Large Language Models (LLMs), Retrieval-Augmented\nGeneration (RAG), AI agents, and prompt engineering techniques.\nCollaborate with cross-functional teams including Product, Data Science, and Engineering to deliver innovative AI-driven capabilities.\nDevelop secure, high-performance REST APIs and microservices.\nOptimise application performance, scalability, and reliability.\nMentor engineers and drive engineering best practices, code quality, and technical excellence.\nStay updated with the latest advancements in AI and apply them to solve real-world business challenges.\n\nRequirements: \n8+ years of experience in backend software development.\nStrong expertise in Java, Spring Boot, and Microservices Architecture.\nHands-on experience with Generative AI, LLMs, Prompt Engineering, RAG, or AI Agent frameworks.\nExperience integrating AI models through APIs such as OpenAI, Azure OpenAI, Vertex AI, or similar platforms.\nStrong knowledge of REST APIs, distributed systems, and scalable system design.\nExperience with cloud platforms (AWS, Azure, or GCP).\nFamiliarity with Docker, Kubernetes, CI/CD pipelines, and DevOps practices.\nStrong problem-solving skills and ability to lead technical initiatives.\n\nGood to Have: \nExperience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.\nKnowledge of vector databases such as Pinecone, Weaviate, Milvus, or ChromaDB.\nExposure to MLOps, model deployment, or AI observability.\nExperience working in Agile development environments.\nSkills\nAI agents, 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