AI Engineer with Java

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.