VP Engineering, AI

Sedgwick

Drive AI engineering strategy and develop scalable AI solutions for Sedgwick’s claims and risk management. Build and mentor a high-performing AI engineering organization for enterprise impact.

Posted 4/26/2026full-timeRemote • Idaho, Louisiana, New York, Tennessee • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

CloudCyber SecurityDistributed SystemsMicroservices

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

flexible work arrangements
professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI engineeringLLM integrationretrieval-augmented generationmulti-agent orchestrationworkflow automationmodel lifecycle managementRAG architecturesvector databasescloud-native architecturesmicroservices design

Soft Skills

leadershipcommunicationchange managementmentoringoperational disciplinetechnical excellencecollaborationfinancial acumenstrategic thinkingalignment