Agentic AI Engineer: LLM-Powered Claims Automation

Sedgwick; Tennessee; On-site; USD 120,000 - 190,000; Full time

Job summary

Sedgwick in Tennessee seeks an Applied & Agentic AI Engineer to architect and deploy AI-powered claim processing and automation. You will design RAG systems, multi-agent workflows, and deterministic outputs across enterprise data, with a focus on reliability and governance.

You'll collaborate with data engineering, claims operations, and security teams to implement scalable microservices, model monitoring, and responsible AI practices within Azure OpenAI environments.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI, Engineering, or related field.
• 5+ years building production-grade AI or advanced software systems.
• 2–4+ years hands-on experience with LLM-powered apps and orchestration layers.
• Strong expertise in retrieval-augmented generation architectures and vector search.

Responsibilities

• Architect and deploy LLM-powered AI solutions for claims intake, policy interpretation, and fraud detection.
• Design end-to-end RAG systems leveraging knowledge bases, SOPs, and historical data.
• Build autonomous agents for multi-step claims processes and secure tool integrations.
• Develop stateful workflow orchestration for context, memory, and task sequencing.

Skills

Python

LLM Apps

Vector search

Multi-agent systems

API design

CI/CD

Azure OpenAI

Containerization

Model monitoring

Responsible AI

Claims domain

Education

Bachelor's or Master’s in CS/AI/Engineering

Tools

Azure OpenAI

Docker

Kubernetes

REST APIs

Git

Job description

Sedgwick in Tennessee seeks an Applied & Agentic AI Engineer to architect and deploy AI-powered claim processing and automation. You will design RAG systems, multi-agent workflows, and deterministic outputs across enterprise data, with a focus on reliability and governance.

You'll collaborate with data engineering, claims operations, and security teams to implement scalable microservices, model monitoring, and responsible AI practices within Azure OpenAI environments.