Senior and Applied/Agentic AI Engineer

Sedgwick; Southaven (MS); Remote; USD 140,000 - 200,000; Full time

Job summary

Sedgwick is seeking an experienced Senior AI Engineer to lead the architecture and delivery of enterprise-grade LLM and agentic AI systems across claims, risk, and operations. You will define technical strategy for RAG, orchestration, and secure tool integration, driving measurable ROI while ensuring governance and compliance.

Join a team that values innovation, accountable AI, and scalable microservices in cloud-native environments, with opportunities to mentor engineers and shape enterprise AI

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.
• 7–10+ years of AI engineering or distributed software architecture experience.
• 3–5+ years designing and deploying LLM-powered systems in production.

Responsibilities

• Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems for claims, risk, and workflows.
• Define technical strategy for RAG, multi-agent orchestration, and automation.
• Design and implement agentic systems with planning, reflection, memory, tool execution.
• Architect memory-aware AI systems for long-running claims processes.
• Build multi-agent collaboration models for coverage analysis, validation, fraud signals, compliance, and decision support.
• Establish orchestration frameworks for task routing, persistence, outputs, and failure handling.
• Design secure tool integration layers to connect agents with claims systems and data services.
• Implement guardrails, schema validation, and output verification to reduce hallucination.
• Lead document intelligence systems for summarization, extraction, discrepancy detection, and data reconstruction.
• Define prompts and reusable reasoning templates for domain-aware outputs.
• Oversee embedding strategies, vector indexing, and retrieval optimization.
• Design evaluation frameworks for reasoning depth, latency, and cost efficiency.

Skills

LLM engineering

Agentic AI

Python

Distributed systems

RAG architectures

Embedding strategies

Vector databases

Multi-agent orchestration

Cloud-native microservices

API integration

Education

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

Tools

Python

Vector databases

Job description

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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

Senior and Applied/Agentic AI Engineer

Job Responsibilities

• Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems that transform claims, risk, and operational workflows.
• Define technical strategy for retrieval-augmented generation (RAG), multi-agent orchestration, and autonomous workflow automation.
• Design and implement advanced agentic systems capable of planning, reasoning, tool selection, execution, reflection, and recovery.
• Architect stateful, memory-aware AI systems that manage long-running claims processes across multiple touchpoints.
• Build multi-agent collaboration models that coordinate coverage analysis, document validation, fraud signals, compliance checks, and decision support.
• Establish orchestration frameworks that manage task routing, context persistence, structured outputs, and failure handling.
• Design secure tool integration layers connecting agents to claims systems, policy platforms, data warehouses, document repositories, and external data services.
• Implement deterministic guardrails, schema validation, and output verification pipelines to reduce hallucination and execution risk.
• Lead development of document intelligence systems leveraging LLMs for summarization, entity extraction, discrepancy detection, and structured data reconstruction.
• Define prompt engineering standards and reusable reasoning templates for consistent, domain-aware outputs.
• Oversee embedding strategies, vector indexing architecture, retrieval optimization, and knowledge grounding approaches.
• Design evaluation frameworks to measure reasoning depth, workflow completion accuracy, hallucination rates, latency, and cost efficiency.
• Implement observability layers that track agent decisions, tool usage, retrieval effectiveness, and drift across models and prompts.
• Drive optimization strategies for token efficiency, caching, batching, and inference scaling.
• Ensure compliance with Responsible AI principles, enterprise governance standards, audit requirements, and regulatory constraints.
• Partner with enterprise architecture, cybersecurity, and data governance teams to define secure deployment patterns.
• Mentor engineers on LLM orchestration patterns, workflow decomposition, and safe agent design.
• Translate executive-level business objectives into scalable AI platform capabilities.
• Lead proof-of-concepts through full production deployment with measurable ROI outcomes.
• Continuously evaluate emerging foundation models, orchestration frameworks, and agent tooling for enterprise readiness.

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.
• Deep expertise in RAG architectures, embedding strategies, vector databases, and retrieval optimization.
• Strong experience designing multi-agent orchestration frameworks and workflow engines.
• Advanced proficiency in Python and enterprise API integration patterns.
• Experience building secure, scalable microservices in cloud-native environments.
• Strong understanding of distributed systems, event-driven architectures, and system reliability principles.
• Experience implementing structured output enforcement, guardrails, and audit logging mechanisms.
• Demonstrated ability to design evaluation and benchmarking frameworks for LLM and agent reliability.
• Experience operating in regulated industries such as insurance, financial services, or healthcare preferred.
• Proven leadership in technical design reviews, architecture governance, and cross-functional collaboration.
• Strong ability to balance innovation with enterprise risk management and operational stability.

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

If you're excited about this role but your experience doesn't align perfectly with every qualification in the job description, consider applying for it anyway! 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.

Sedgwick is the world’s leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The company’s expertise, combined with the most advanced AI-enabled technology available, sets the standard for solutions in claims administration, loss adjusting, benefits administration, and product recall. With over 33,000 colleagues and 10,000 clients across 80 countries, Sedgwick provides unmatched perspective, caring that counts, and solutions for the rapidly changing and complex risk landscape. For more, see sedgwick.com