AI Engineer with Java

Job description

Job Summary Job Description: A highly skilled AI Engineer to develop AI use cases using Gen AI and Agentic AI technologies. The ideal candidate will have deep expertise in Java, enterprise-grade frameworks, and next-generation AI integrations using platforms such as Spring AI, Spring Batch, and Quarkus. This role focuses on designing intelligent, autonomous systems that transform insurance workflows, leveraging Azure-based AI services and scalable Java architectures. Responsibilities • AI Agentic System Development: Design, implement, and orchestrate Agentic AI systems using LangChain4j, Spring AI, and other JVM-based frameworks to enable autonomous reasoning, decision-making, and task execution across insurance processes such as claims triage, underwriting, and customer service. • Generative AI Integration: Develop RAG pipelines and LLM-based reasoning components using Java to deliver accurate, context-aware insights grounded in insurance documentation and structured data. • API Service Engineering: Build and optimize secure, high-performance RESTful APIs in Java/Spring Boot to interface with generative models, knowledge bases, and insurance core systems. • Cloud-Native AI Deployment: Containerize and deploy AI workloads on Microsoft Azure, leveraging Azure OpenAI Service, Azure ML, and App Services for robust scalability, monitoring, and compliance. • System Integration Collaboration: Work closely with data engineers, solution architects, and business analysts to embed AI capabilities within existing insurance ecosystems integrating policy data, claims systems etc. Requirements • Languages Tools: Advanced proficiency in Java, with strong understanding of concurrency, memory management, and JVM optimization. • Frameworks: Experience with LangChain4j, Spring AI, Spring Batch, Quarkus for AI application development. • AI Expertise: Demonstrated experience with Gen AI, LLM integration, and Agentic architectures. • Cloud Knowledge: Familiarity with Azure AI ecosystem (Azure ML, Cognitive Search, OpenAI Service). • Development Practices: Proficiency in API design, unit testing, and CI/CD pipelines using tools such as Maven, Gradle, or GitHub Actions. • Collaboration Documentation: Strong communication skills and ability to produce technical design documents and architecture diagrams. Nice to Haves • Experience developing AI orchestration pipelines or knowledge graphdriven retrieval systems. • Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and semantic search indexing. • Experience fine-tuning or serving LLMs through Java-based inference layers. • Exposure to AIOps practices (e.g., monitoring, retraining workflows). • Understanding of core insurance platforms such as Guidewire, Duck Creek, or Sapiens. • Interest in open-source AI development within the Java community.