Hiring: Applied & Agentic AI Engineer Company: Sedgwick Location: Tennessee, United States Job Posted Time: 2026-09-16 15:17:02 Target Skills & Keywords : AI, Azure, CI/CD, Event-Driven, Feature Store, LLM, Microservices, Python, RAG, Systems Design About the job Experience: •5+ years of experience building production-grade AI or advanced software systems. •4+ years of hands-on experience with LLM-powered applications and orchestration layers. Required Skills: •Architect and deploy LLM-powered and agentic AI solutions that transform claims intake, policy interpretation, fraud detection, and resolution workflows. •Design end-to-end retrieval-augmented generation (RAG) systems leveraging enterprise knowledge bases, policy documents, SOPs, and historical claims data. •Build autonomous and semi-autonomous agents capable of reasoning, planning, and executing multi-step claims processes. •Develop stateful workflow orchestration layers that manage context, memory, and task sequencing across interactions. •Implement planning and reflection loops that decompose complex claims scenarios into structured subtasks. •Enable dynamic tool use through function calling and secure API integrations with claims systems, CRM platforms, document repositories, and analytics tools. •Develop document intelligence pipelines using LLMs for summarization, entity extraction, classification, validation, and timeline reconstruction. •Design structured prompt frameworks that enforce deterministic outputs and domain-aware reasoning. Qualifications: •Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related field. •2–4+ years of hands-on experience with LLM-powered applications and orchestration layers. •Strong expertise in retrieval-augmented generation architectures and vector search systems. •Comprehensive expertise in planning loops, contextual memory, and tool-augmented LLM reasoning. •Strong proficiency in Python and API-driven system design. •Operational familiarity with Azure OpenAI or similar enterprise LLM environments. •Understanding of distributed systems, microservices, and event-driven architectures. •Strong knowledge of evaluation methodologies for LLM reliability and agent performance. •Demonstrated capacity to translate complex operational workflows into scalable, AI-driven autonomous systems. Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!