Location(s)
Alpharetta, Georgia, Annapolis, Maryland, Birmingham, Alabama, Boston, Massachusetts, Buffalo, New York, Chicago, Illinois, Dallas, Texas, Des Moines, Iowa, Dover, Delaware, Downers Grove, Illinois, Harrisburg, Pennsylvania, Hartford, Connecticut, Indianapolis, Indiana, Jacksonville, Florida, Las Vegas, Nevada, Little Rock, Arkansas, Oklahoma City, Oklahoma, Phoenix, Arizona, Raleigh, North Carolina, Remote-GA, Remote-IA, Remote-IL, Remote-MI, Remote-NJ, St. Louis, Missouri

Details

The SVP, Chief Technology Officer (CTO) is the executive responsible for defining and executing the enterprise technology strategy through four strategic pillars:

• Cloud & Platform Engineering
• Enterprise Data Engineering
• Artificial Intelligence & Intelligent Automation
• Enterprise Architecture & Technology Innovation

The CTO is accountable for building and operating the secure, scalable, cloud-native technology platforms that enable the business to innovate, modernize, and compete. This includes enterprise cloud infrastructure, developer platforms, data platforms, AI platforms, integration capabilities, and shared technology services that support all business functions.

A critical responsibility of this role is ensuring Artificial Intelligence delivers measurable business value. The CTO partners with executive leadership to identify opportunities where AI can fundamentally redesign business processes, improve customer and employee experiences, accelerate decision-making, and create competitive advantage. Success is measured not by AI experimentation, but by enterprise adoption, business transformation, and quantifiable business outcomes.

The CTO works in partnership with the CIO to shape the long-term technology vision while ensuring technology investments improve enterprise agility, resiliency, operational efficiency, and innovation.

Key Responsibilities

Enterprise Technology Strategy

• Develop and execute the enterprise technology strategy aligned with business objectives and long-term growth.
• Establish technology roadmaps that modernize enterprise capabilities through cloud-native platforms, automation, data, and AI.
• Advise the organization on emerging technologies, technology investments, and innovation opportunities.
• Drive enterprise technology standards, governance, architecture, and technology lifecycle management.

Cloud & Platform Engineering

Lead the strategy, engineering, and operation of enterprise technology platforms, including:

• Public and hybrid cloud infrastructure
• Platform Engineering
• Kubernetes and container platforms
• Infrastructure as Code (IaC)
• DevSecOps and CI/CD platforms
• Site Reliability Engineering (SRE)
• Enterprise observability and monitoring
• Identity and shared platform services
• FinOps and cloud optimization

Build highly automated, resilient, secure, and scalable technology platforms that accelerate software delivery while improving operational excellence and reducing total cost of ownership.

Enterprise Data Engineering

Define and lead the enterprise Data Engineering strategy supporting analytics, operational reporting, AI, and digital products.

Responsibilities include:

• Modern cloud-based data platforms
• Enterprise data lakehouse architecture
• Data governance and metadata management
• Data quality and lineage
• Master Data Management
• Enterprise data security

Demonstrated expertise is required across multiple enterprise data integration patterns including:

• Batch processing
• API-based integration
• Event-driven architectures
• Real-time streaming platforms

Ensure enterprise data is trusted, governed, secure, reusable, and accessible to support business intelligence and AI initiatives.

Artificial Intelligence & Intelligent Automation

Develop and execute the enterprise AI strategy focused on measurable business value creation.

Responsibilities include:

• Identify high-value AI opportunities in partnership with business leaders.
• Consult with business executives to redesign business processes that leverage AI rather than simply automating existing human workflows.
• Lead enterprise implementation of Generative AI, Machine Learning, Intelligent Automation, and Agentic AI capabilities.
• Build and operate enterprise AI platforms supporting secure and scalable AI adoption.
• Establish Responsible AI governance, model lifecycle management, and AI risk management.
• Create repeatable frameworks for identifying, prioritizing, implementing, and scaling AI use cases across the enterprise.
• Drive enterprise AI literacy through executive education, workforce training, change management, communications, and adoption programs.
• Measure AI success through quantifiable business outcomes including productivity improvements, expense reduction, revenue growth, customer satisfaction, and operational efficiency.

Candidates must demonstrate a proven track record of leading enterprise AI implementations that progressed beyond pilot programs to production deployment with measurable business value.

Enterprise Architecture & Technology Innovation

Lead Enterprise Architecture to ensure technology investments create reusable enterprise capabilities rather than siloed solutions.

Drive innovation through:

• Emerging technology evaluation
• Technology incubation
• Strategic partnerships
• Cloud hyperscaler relationships
• AI ecosystem partnerships
• Technology standards and reference architectures

Guide enterprise modernization initiatives while ensuring technology investments remain aligned with business strategy.

Executive Leadership & Governance

Build and lead high-performing organizations across:

• Cloud & Platform Engineering
• Enterprise Data Engineering
• Enterprise Architecture
• AI & Intelligent Automation
• Technology Innovation

Establish a culture of engineering excellence, innovation, accountability, continuous learning, and business partnership.

Oversee technology investment planning, vendor strategy, technology risk, operational resiliency, regulatory compliance, and executive performance reporting.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline; Master's degree, MBA, or advanced technical degree preferred.
• 15+ years of progressive technology leadership with at least 5 years in executive leadership roles within large, regulated enterprises.
• Deep expertise leading Cloud & Platform Engineering organizations supporting enterprise-scale digital capabilities.
• Demonstrated success implementing cloud-native platforms utilizing Infrastructure as Code, Platform Engineering, DevSecOps, Kubernetes, observability, automation, and Site Reliability Engineering.
• Extensive experience leading Enterprise Data Engineering organizations, including modern cloud data platforms and enterprise integration using batch, APIs, event-driven architectures, and streaming technologies.
• Proven success delivering enterprise AI solutions that achieved measurable business outcomes through production implementation, organizational adoption, and business process transformation.
• Demonstrated leadership in AI strategy, AI governance, responsible AI, enterprise AI platforms, AI literacy, organizational change management, and executive consulting.
• Strong understanding of cloud security, enterprise architecture, technology governance, and regulatory environments within financial services or insurance.
• Exceptional executive communication skills with the ability to influence Boards of Directors, executive leadership teams, regulators, and strategic technology partners.
• Proven ability to attract, develop, and inspire world-class engineering and technology leaders while fostering a culture of innovation, accountability, and continuous improvement.
• This role can work at a Kemper office or remotely from a US based home.

The range for this position is $250,000 to $350,000. When determining candidate offers, we consider experience, skills, education, certifications, and geographic location among other factors. This job is eligible for an annual discretionary bonus, equity and Kemper benefits (Medical, Dental, Vision, PTO, 401k, etc.).

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