AI Solutions Engineer

About Sedgwick

Join Sedgwick and be part of something truly meaningful. Our 33,000 colleagues support people across the globe during unexpected challenges. Grow your career in a caring culture that prioritizes work-life balance. At Sedgwick, the potential for achievement is limitless.

Recognized by Newsweek as America's Greatest Workplaces and certified as a Great Place to Work®, Sedgwick is also among the Fortune Best Workplaces in Financial Services & Insurance.

Sedgwick is an Equal Opportunity Employer and a Drug-Free Workplace. If you feel excited about this role but don't meet all the listed qualifications, we encourage you to apply anyway! We are committed to building a diverse and inclusive workplace that values unique skills and experiences.

As the world's leading risk and claims administration partner, Sedgwick assists clients in navigating the unexpected. Our advanced AI-enabled technology, combined with expert knowledge, sets us apart in claims administration and related services. With over 33,000 colleagues and 10,000 clients across 80 countries, we deliver unmatched perspectives, support, and solutions in a rapidly changing risk landscape.

Role Overview

AI Solutions Engineer

Key Responsibilities

• Create and deploy LLM-powered AI solutions that enhance claims intake, policy interpretation, fraud detection, and resolution processes.
• Design comprehensive retrieval-augmented generation systems using enterprise knowledge bases, policy documents, SOPs, and historical claims data.
• Develop both autonomous and semi-autonomous agents to effectively handle multi-step claims procedures.
• Build robust workflow orchestration layers that maintain context, memory, and task sequencing throughout interactions.
• Implement planning and reflection mechanisms that break down intricate claims scenarios into structured subtasks.
• Enable dynamic tool utilization through function calling and secure API integrations with various claims systems and analytics tools.
• Create document intelligence pipelines using LLMs for tasks such as summarization, entity extraction, classification, validation, and reconstructing timelines.
• Develop structured prompt frameworks to ensure deterministic outputs and domain-aware reasoning.
• Build multi-agent systems for coordinating document reviews, compliance checks, and decision support.
• Implement human-in-the-loop checkpoints for the escalation and review of AI decisions.
• Design guardrails, output validation layers, and strategies to mitigate erroneous AI outputs.
• Ensure structured outputs through schemas, type validation, and deterministic post-processing logic.
• Optimize token usage, inference latency, and cloud infrastructure costs.
• Deploy scalable AI microservices utilizing containerization and cloud-native architectures.
• Monitor model performance for drift, retrieval quality, reasoning failures, and workflow disruptions.
• Maintain comprehensive audit logs detailing model decisions and agent activities.
• Establish evaluation frameworks to assess reasoning accuracy, workflow completion rates, and overall system reliability.
• Collaborate with data engineering teams to create embedding pipelines and vector indexing strategies.
• Ensure compliance with Responsible AI standards, data privacy regulations, and governance policies.
• Partner with claims operations to integrate AI capabilities within adjuster and supervisor workflows.
• Assess business impacts through metrics like cycle-time reduction and operational efficiency improvements.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Engineering, or a related field.
• 5+ years of experience in building production-grade AI or advanced software systems.
• 2-4+ years of practical experience with LLM-based applications and orchestration layers.
• Proficiency in retrieval-augmented generation architectures and vector search systems.
• Experience in designing and implementing multi-agent systems and workflow orchestration engines.
• Deep understanding of planning loops, contextual memory, and tool-augmented reasoning.
• Strong programming skills in Python and experience with API-driven system design.
• Experience with enterprise platform integration and building secure connectors.
• Familiar with Azure OpenAI or similar enterprise LLM environments.
• Experience deploying containerized services and managing CI/CD pipelines.
• Knowledge of distributed systems, microservices, and event-driven architectures.
• Proven experience in implementing quality controls, access measures, and auditing mechanisms.
• Familiarity with evaluation methodologies for assessing LLM reliability and agent performance.
• Prior experience in the insurance, claims, healthcare, or regulated industries is preferred.
• Ability to translate complex operational workflows into scalable, AI-driven solutions.