Senior Applied & Agentic AI Engineer

By joining Sedgwick, you'll be part of something truly meaningful. Itu2019s 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, thereu2019s no limit to what you can achieve. Newsweek Recognizes Sedgwick as Americau2019s Greatest Workplaces National Top Companies Certified as a Great Place to Worku00ae Fortune Best Workplaces in Financial Services & Insurance Senior Applied & Agentic AI Engineer Job Responsibilities u00b7 Lead the architecture and delivery of enterprise-grade LLM and agentic AI systems that transform claims, risk, and operational workflows. u00b7 Define technical strategy for retrieval-augmented generation (RAG), multi-agent orchestration, and autonomous workflow automation. u00b7 Design and implement advanced agentic systems capable of planning, reasoning, tool selection, execution, reflection, and recovery. u00b7 Architect stateful, memory-aware AI systems that manage long-running claims processes across multiple touchpoints. u00b7 Build multi-agent collaboration models that coordinate coverage analysis, document validation, fraud signals, compliance checks, and decision support. u00b7 Establish orchestration frameworks that manage task routing, context persistence, structured outputs, and failure handling. u00b7 Design secure tool integration layers connecting agents to claims systems, policy platforms, data warehouses, document repositories, and external data services. u00b7 Implement deterministic guardrails, schema validation, and output verification pipelines to reduce hallucination and execution risk. u00b7 Lead development of document intelligence systems leveraging LLMs for summarization, entity extraction, discrepancy detection, and structured data reconstruction. u00b7 Define prompt engineering standards and reusable reasoning templates for consistent, domain-aware outputs. u00b7 Oversee embedding strategies, vector indexing architecture, retrieval optimization, and knowledge grounding approaches. u00b7 Design evaluation frameworks to measure reasoning depth, workflow completion accuracy, hallucination rates, latency, and cost efficiency. u00b7 Implement observability layers that track agent decisions, tool usage, retrieval effectiveness, and drift across models and prompts. u00b7 Drive optimization strategies for token efficiency, caching, batching, and inference scaling. u00b7 Ensure compliance with Responsible AI principles, enterprise governance standards, audit requirements, and regulatory constraints. u00b7 Partner with enterprise architecture, cybersecurity, and data governance teams to define secure deployment patterns. u00b7 Mentor engineers on LLM orchestration patterns, workflow decomposition, and safe agent design. u00b7 Translate executive-level business objectives into scalable AI platform capabilities. u00b7 Lead proof-of-concepts through full production deployment with measurable ROI outcomes. u00b7 Continuously evaluate emerging foundation models, orchestration frameworks, and agent tooling for enterprise readiness. Qualifications u00b7 Bacheloru2019s or Masteru2019s degree in Computer Science, Artificial Intelligence, Engineering, or related discipline. u00b7 7u201310+ years of experience in AI engineering, machine learning systems, or distributed software architecture. u00b7 3u20135+ years designing and deploying LLM-powered systems in production environments. u00b7 Demonstrated experience architecting full agentic AI systems with planning, reflection, memory, and tool execution components. u00b7 Deep expertise in RAG architectures, embedding strategies, vector databases, and retrieval optimization. u00b7 Strong experience designing multi-agent orchestration frameworks and workflow engines. u00b7 Advanced proficiency in Python and enterprise API integration patterns. u00b7 Experience building secure, scalable microservices in cloud-native environments. u00b7 Strong understanding of distributed systems, event-driven architectures, and system reliability principles. u00b7 Experience implementing structured output enforcement, guardrails, and audit logging mechanisms. u00b7 Demonstrated ability to design evaluation and benchmarking frameworks for LLM and agent reliability. u00b7 Experience operating in regulated industries such as insurance, financial services, or healthcare preferred. u00b7 Proven leadership in technical design reviews, architecture governance, and cross-functional collaboration. u00b7 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 worldu2019s leading risk and claims administration partner, which helps clients thrive by navigating the unexpected. The companyu2019s 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. 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Created: 2026-03-11