Hybrid SVP AI Engineering

at Sedgwick

• Job title: SVP AI Engineering
• Job type: Full Time
• Experience level: Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Cloud, Cyber Security, Distributed Systems, Microservices
• Location requirements: Hybrid, United States

About the role

• SVP AI Engineering leading enterprise AI engineering strategy and solutions for Sedgwick's global operations. Driving technical excellence and operational discipline in claims and risk management.

Responsibilities

• Define and execute the enterprise AI engineering strategy aligned to Sedgwick’s claims, risk, and client service transformation goals.
• Lead the architecture, development, and deployment of applied AI and agentic AI solutions across global operations.
• Build and scale a high-performing AI engineering organization, including Applied AI Engineers, Agentic AI Engineers, ML Engineers, and AI Platform teams.
• Establish standards for LLM integration, retrieval-augmented generation (RAG), multi-agent orchestration, workflow automation, and model lifecycle management.
• Oversee the design of autonomous and semi-autonomous AI systems that support claims intake, coverage analysis, fraud detection, compliance review, and operational optimization.
• Drive enterprise architecture decisions for AI platforms, including model hosting, orchestration layers, vector databases, evaluation frameworks, and observability tooling.
• Ensure scalable, secure integration of AI systems with claims platforms, policy systems, document repositories, and enterprise data environments.
• Define and enforce engineering best practices for prompt engineering, tool use, memory design, guardrails, structured outputs, and deterministic validation.
• Establish governance frameworks for Responsible AI, explainability, auditability, and regulatory compliance.
• Partner with cybersecurity, legal, compliance, and data governance teams to mitigate AI-related operational and regulatory risks.
• Develop robust evaluation and benchmarking methodologies to measure reasoning quality, workflow completion rates, hallucination risk, and system reliability.
• Oversee AI production operations including performance monitoring, drift detection, cost management, and service reliability.
• Translate executive-level business priorities into scalable AI platform capabilities and delivery roadmaps.
• Collaborate with Claims Operations, IT, Digital, and Product teams to identify high-impact AI use cases and drive measurable ROI.
• Lead build-versus-buy decisions for AI tooling, foundation models, orchestration frameworks, and enterprise integrations.
• Manage vendor relationships related to AI platforms, cloud providers, and model providers.
• Drive adoption of AI solutions across adjusters, supervisors, and client-facing teams through strong partnership and change management alignment.
• Mentor engineering leaders and establish a strong culture of technical excellence, innovation, and operational discipline.
• Present AI strategy, progress, risks, and outcomes to executive leadership and board-level stakeholders.
• Develop long-term AI capability roadmaps that position Sedgwick as a technology leader in claims and risk management.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Engineering, or related field; advanced degree preferred.
• 10+ years of experience in software engineering, AI engineering, or platform architecture.
• 5+ years of leadership experience managing high-performing technical teams.
• Demonstrated experience deploying LLM-powered systems and agentic AI solutions in enterprise environments.
• Deep expertise in RAG architectures, vector databases, orchestration frameworks, and workflow automation systems.
• Strong understanding of distributed systems, cloud-native architectures, and microservices design.
• Experience building secure integrations with enterprise systems and legacy platforms.
• Proven ability to design and implement AI governance, auditability, and Responsible AI frameworks.
• Experience operating in regulated industries such as insurance, healthcare, or financial services preferred.
• Strong financial and operational acumen with the ability to manage budgets and measure ROI.
• Ability to communicate complex AI concepts to non-technical executives and business stakeholders.
• Demonstrated track record of delivering large-scale, production AI systems with measurable business impact.
• Strong leadership presence with the ability to drive alignment across cross-functional enterprise teams.

Benefits

• Health insurance
• 401(k) matching
• Flexible work hours
• Paid time off
• Remote work options