Risepoint is an education technology company that helps regional universities launch and grow online programs for modern learners. Risepoint supports more than 100 universities and colleges across five countries, with programs concentrated in high-demand fields including nursing, healthcare, teaching, business, technology, and public service. Our suite of products and services supports the full student journey and each university’s long-term goals. Together, we increase access to affordable education that delivers a strong return on investment for learners and meets employer and community needs. Learn more at risepoint.com.
Role Overview
Risepoint is poised to transform the organization using technology and an AI-first mindset. We are seeking a visionary and execution-focused VP, AI Transformation and Enterprise Architecture, to lead the next phase of our AI-powered transformation. This executive will be responsible for working with cross functional teams for building and scaling AI-driven products, driving enterprise-wide AI adoption, shaping technology strategy and architecture, and leading complex technology integration initiatives, including post-merger and acquisition (M&A) integrations.
This role requires a unique blend of deep engineering leadership, enterprise architecture expertise, AI innovation, and strategic consulting capabilities. The ideal candidate is equally comfortable defining long-term technology strategy, building high-performing engineering organizations, and rolling up their sleeves to solve ambiguous, high-impact business challenges.
The VP will partner closely with executive leadership, product, engineering, operations, and business teams to accelerate AI adoption, modernize technology platforms, and establish a scalable architecture foundation for future growth.
Over time, the scope of this role is expected to expand to include direct ownership of the engineering and product function for a core application area, giving the VP full accountability for the strategy, roadmap, delivery, and operation of that portfolio.
Key Responsibilities
Technology AI Transformation Leadership
- Lead and scale AI adoption across all technology teams at Risepoint.
- Establish engineering best practices, operating models, and delivery frameworks for AI and machine learning initiatives.
- Oversee the design, development, deployment, and lifecycle management of Agentic AI, Generative AI, and intelligent automation solutions.
- Drive technical excellence in AI application development, model integration, orchestration frameworks, evaluation, observability, and governance.
Enterprise AI Transformation & Adoption
- Define and execute the enterprise-wide AI strategy, driving the adoption and integration of AI across technology, operations, and business functions.
- Partner with executive leadership and cross-functional stakeholders to identify, prioritize, and scale high-impact AI initiatives that improve operational efficiency, customer experience, employee productivity, and business outcomes.
- Lead the development and implementation of AI governance, architecture standards, risk management frameworks, and responsible AI practices to ensure scalable and sustainable adoption.
- Collaborate across Product, Operations, Marketing, Finance, HR, and other business units to embed AI capabilities into core business processes, workflows, and customer-facing solutions.
- Serve as a strategic advisor and thought leader on emerging AI technologies, translating complex technical concepts into clear business value and executive-level recommendations.
- Champion organizational change management, workforce enablement, and AI literacy initiatives to accelerate enterprise-wide adoption and maximize value realization.
Enterprise Architecture
- Own and evolve the company's enterprise architecture strategy, ensuring alignment with business objectives and growth plans.
- Establish architecture principles, standards, and governance processes across applications, data, integrations, infrastructure, and AI platforms.
- Create scalable technology roadmaps that support innovation while maintaining operational excellence and security.
- Ensure interoperability, scalability, reliability, and maintainability across the enterprise technology landscape.
Drive M&A Integrations
- Lead technology due diligence and integration planning for mergers, acquisitions, and strategic partnerships.
- Develop and execute post-M&A technology integration strategies, including systems consolidation, data migration, application rationalization, and architecture alignment.
- Partner with business leaders to accelerate value realization from acquisitions while minimizing operational disruption.
- Establish repeatable integration frameworks and playbooks to support future M&A activity.
Engineering and Product Ownership (Future Scope)
- Assume full ownership of the engineering and product function for a designated application area as the organization scales, including delivery, operations, and long-term platform direction.
- Own the product vision, roadmap, and prioritization for that area, from discovery and requirements through release, adoption, and ongoing support.
- Build, lead, and develop the engineering and product management teams supporting the application area, including org design, hiring, coaching, and performance management.
- Own budget, vendor relationships, and resource allocation for the area, and make build-versus-buy decisions that balance speed, cost, and long-term flexibility.
- Set and enforce standards for quality, reliability, security, and performance across the applications in scope, with clear service levels and operational metrics.
- Partner with business owners and end users to define success measures, then report on adoption, value delivered, and roadmap progress to executive leadership.
- Use the application area as a proving ground for the enterprise AI and architecture standards established in this role, embedding AI capabilities directly into the product experience.
- Maintain enterprise alignment as the scope grows, ensuring decisions made within the application area reinforce rather than fragment the broader architecture.
Qualifications
- 15+ years of progressive technology leadership experience, including leading large-scale engineering organizations.
- Proven experience building and scaling software engineering teams and technology organizations.
- Demonstrated success delivering AI-powered products and platforms in production environments.
- Experience leading enterprise-wide technology transformation initiatives.
- Deep expertise in enterprise architecture, technology strategy, and systems integration.
- Significant experience managing complex cross-functional programs involving both technical and business stakeholders.
- Experience leading technology integration efforts associated with mergers, acquisitions, or large-scale organizational transformations.
- Passion for AI-first strategies and leveraging emerging technologies to accelerate business outcomes.
- Experience in fast-moving industries and organizations that have technology systems supporting multiple brands within the same ecosystem.
- Experience owning both engineering and product management functions for an application or product portfolio, including roadmap ownership and budget accountability.
Preferred Experience
- Background in top-tier management consulting (e.g., McKinsey, Bain, BCG, Accenture, Deloitte, EY-Parthenon, or similar).
- Experience in the Higher Education industry
- Hands-on experience with Agentic AI architectures, autonomous systems, multi-agent orchestration frameworks, and Generative AI platforms.
- Experience deploying and scaling LLM-based applications and AI-driven automation solutions.
- Expertise across modern cloud platforms, data platforms, APIs, integration architectures, and enterprise SaaS ecosystems.
- Experience operating within high-growth, rapidly evolving organizations.
Technical Expertise
- Agentic AI and Generative AI architectures and implementation
- Large Language Models (LLMs), RAG, vector databases, and AI orchestration frameworks
- AI platform engineering, MLOps, LLMOps, and model lifecycle management
- Enterprise architecture and technology governance
- Cloud-native application architectures and distributed systems
- Data platforms, analytics, and integration architectures
- API strategies, event-driven architectures, and middleware platforms
- Cybersecurity, compliance, and responsible AI practices
Leadership Competencies
The successful candidate will demonstrate:
- Strategic Vision: Ability to define long-term technology and AI strategy aligned with business objectives.
- Executive Influence: Strong executive presence with the ability to influence senior stakeholders across the organization.
- Builder Mindset: Proven ability to create structure in ambiguous environments and build organizations, processes, and platforms from the ground up.
- Transformation Leadership: Experience leading large-scale organizational and technology change initiatives.
- Consultative Problem Solving: Ability to navigate complex business challenges and translate strategy into execution.
- Operational Excellence: Strong focus on execution, accountability, and measurable outcomes.
- Entrepreneurial Agility: Thrives in fast-paced environments with evolving priorities and significant white-space opportunities.
Risepoint is an equal-opportunity employer and supports a diverse and inclusive workforce.
