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Vice President Model Risk Management Jobs in Kansas

VP AI Engineering

Overland Park, KS

$170K - $219K/yr

Manage vendor relationships related to AI platforms, cloud providers, and model providers. * Drive ... risk management. Qualifications * Bachelor's or Master's degree in Computer Science, Artificial ...

VP AI Engineering

Wichita, KS

$177K - $229K/yr

Manage vendor relationships related to AI platforms, cloud providers, and model providers. * Drive ... risk management. Qualifications * Bachelor's or Master's degree in Computer Science, Artificial ...

... risk management, and help the organization with its commitment to culture and employee experience. All other duties and responsibilities, as assigned by the President of FUJIFILM Holdings America ...

... risk plan. * Approve budgets and capital allocations; coordinate budgetary control systems and ... Build capacity and utilization models to identify constraints and unlock excess capacity to support ...

Drive consistent pipeline development, opportunity management, and forecast accuracy across the ... model for a "leaned in" approach to AI as a senior leader on the team * Identify and implement AI ...

Drive consistent pipeline development, opportunity management, and forecast accuracy across the ... model for a "leaned in" approach to AI as a senior leader on the team * Identify and implement AI ...

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Vice President Model Risk Management information

What is the difference between Vice President Model Risk Management vs Model Validation Analyst?

AspectVice President Model Risk ManagementModel Validation Analyst
CredentialsAdvanced degrees (e.g., MBA, PhD), certifications like FRM or CFABachelor's or Master's in finance, statistics, or related fields; certifications like FRM or CFA often preferred
Work EnvironmentStrategic leadership, cross-department collaboration, executive-level reportingAnalytical, detail-oriented work focused on model testing and validation
Employer & Industry UsageFinancial institutions, banks, asset managers, regulatory bodiesFinancial firms, risk management teams, model development groups

The Vice President Model Risk Management oversees the entire model risk framework, focusing on strategy, governance, and high-level risk assessment. In contrast, the Model Validation Analyst conducts detailed testing and validation of models to ensure accuracy and compliance. While both roles require strong quantitative skills and relevant certifications, the VP role is more strategic and managerial, whereas the analyst role is more technical and operational.

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What job categories do people searching Vice President Model Risk Management jobs in Kansas look for? The top searched job categories for Vice President Model Risk Management jobs in Kansas are:
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VP AI Engineering

VP AI Engineering

Sedgwick

Overland Park, KS

$170K - $219K/yr

Full-time

Posted 29 days ago


Sedgwick rating

7.5

Company rating: 7.5 out of 10

Based on 308 frontline employees who took The Breakroom Quiz

186th of 261 rated insurance


Job description

VP AI Engineering leads the enterprise AI engineering strategy aligned to Sedgwick’s claims, risk, and client service transformation goals. The role involves overseeing AI architecture, development, deployment, governance, and integration across global operations, driving adoption, and partnering with cross‑functional teams to deliver measurable ROI.

Job 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.
Qualifications
  • 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.

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

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