Remote Senior AI Engineer: Agentic & LLM Architect

Sedgwick; Biloxi (MS); On-site; USD 150,000 - 210,000; Full time

Job summary

Sedgwick is seeking a senior AI engineer to lead the architecture and deployment of enterprise-grade LLM-powered and agentic AI systems. You will shape RAG strategies, multi-agent orchestration, and secure integrations across claims, risk, and operations.

Qualified candidates bring 7–10+ years in AI/distributed architectures, deep expertise in Python, and hands-on experience with memory, tool execution, and governance frameworks. Remote-friendly with a strong culture of innovation.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.
• 7–10+ years of experience in AI engineering, machine learning systems, or distributed software architecture.
• 3–5+ years designing and deploying LLM-powered systems in production environments.
• Demonstrated experience architecting full agentic AI systems with planning, reflection, memory, and tool execution components.

Responsibilities

• Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems across claims, risk, and operations.
• Define technical strategy for retrieval-augmented generation, multi-agent orchestration, and autonomous workflow automation.
• Design and implement advanced agentic systems with planning, reasoning, tool selection, execution, reflection, and recovery.
• Architect memory-aware AI systems that manage long-running processes across multiple touchpoints.
• Build multi-agent collaboration models coordinating coverage analysis, document validation, fraud signals, compliance checks, and decision support.

Skills

Python

LLM orchestration

RAG architecture

Vector databases

Multi-agent orchestration

Cloud-native microservices

Distributed systems

APIs

Guardrails & audit logs

Education

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

Tools

None

Job description

Sedgwick is seeking a senior AI engineer to lead the architecture and deployment of enterprise-grade LLM-powered and agentic AI systems. You will shape RAG strategies, multi-agent orchestration, and secure integrations across claims, risk, and operations.

Qualified candidates bring 7–10+ years in AI/distributed architectures, deep expertise in Python, and hands-on experience with memory, tool execution, and governance frameworks. Remote-friendly with a strong culture of innovation.