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Strong employer brand, remote role, and metro context increase candidate competition despite niche Java-Agentic AI skills.
Core AI and JVM engineering skills transferable across industries, with some insurance domain knowledge preferred.
Mandatory ML/AI, Java, LangChain4j, Azure, and CI/CD experience creates strict technical filters.
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Design and develop AI Agentic systems using Java frameworks like LangChain4j and Spring AI to automate insurance workflows including claims triage and underwriting.
Implement and integrate Generative AI solutions (RAG pipelines, LLM reasoning) grounded in insurance data to provide context-aware insights.
Build scalable, secure RESTful APIs and deploy AI workloads on Microsoft Azure using services like Azure ML and Azure OpenAI Service.
Advanced proficiency in Java including concurrency, memory management, and JVM optimization.
Experience with AI and Java frameworks such as LangChain4j, Spring AI, Spring Batch, and Quarkus.
Familiarity with Azure AI ecosystem components (Azure ML, Cognitive Search, Azure OpenAI Service).
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in AI engineering within the insurance domain, specifically developing autonomous AI agents and generative AI integrations.
Capable of driving cloud-native AI deployments and API engineering in enterprise environments.
Comfortable collaborating with cross-functional teams such as data engineers, solution architects, and business analysts to integrate AI within complex insurance systems.