Applied & Agentic AI Engineer

Sedgwick is a leading claims management services company that values a caring culture and work-life balance. They are seeking an Applied & Agentic AI Engineer to architect and deploy AI solutions that enhance claims processing and operational workflows through advanced technologies like LLMs and agentic systems.

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

Requirements:

• 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
• Ability to translate complex operational workflows into scalable, AI-driven autonomous systems
• Experience in insurance, claims, healthcare, or other regulated industries