Applied & Agentic AI Engineer

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

By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Applied & Agentic AI Engineer

Job Responsibilities

• 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.
• Build multi-agent systems that coordinate document review, coverage analysis, compliance checks, and decision support.
• Implement human-in-the-loop checkpoints for escalation, review, and override of AI-driven decisions.
• Develop guardrails, output validation layers, and hallucination mitigation strategies.
• Enforce structured outputs using schemas, type validation, and deterministic post-processing logic.
• Optimize token consumption, inference latency, and cloud infrastructure costs.
• Deploy scalable AI microservices using containerization and cloud-native architectures.
• Implement monitoring for model drift, retrieval quality degradation, reasoning failures, and workflow breakdowns.
• Maintain detailed audit logs of model decisions, agent reasoning steps, and tool executions.
• Develop evaluation frameworks to test reasoning accuracy, workflow completion rates, and system reliability.
• Collaborate with data engineering to build embedding pipelines, feature stores, and vector indexing strategies.
• Ensure compliance with Responsible AI standards, data privacy regulations, and enterprise governance policies.
• Partner with claims operations leadership to embed AI capabilities directly into adjuster and supervisor workflows.
• Measure business impact through cycle-time reduction, automation coverage, fraud detection lift, and operational efficiency gains.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related field.
• 5+ years of experience building production-grade AI or advanced software systems.
• 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.
• Experience designing and implementing multi-agent systems and workflow orchestration engines.
• Deep understanding of planning loops, contextual memory, and tool-augmented LLM reasoning.
• Strong proficiency in Python and API-driven system design.
• Experience integrating enterprise platforms and building secure connectors.
• Familiarity with Azure OpenAI or similar enterprise LLM environments.
• Experience deploying containerized services and managing CI/CD pipelines.
• Understanding of distributed systems, microservices, and event-driven architectures.
• Experience implementing guardrails, access controls, and auditability mechanisms.
• Strong knowledge of evaluation methodologies for LLM reliability and agent performance.
• Experience in insurance, claims, healthcare, or other regulated industries preferred.
• Ability to translate complex operational workflows into scalable, AI-driven autonomous systems.

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace.

Sedgwick is building a diverse, equitable, and inclusive workplace and recognizes that each person possesses a unique combination of skills, knowledge, and experience. You may be just the right candidate for this or other roles.