VP, AI Transformation & Enterprise Architecture

Risepoint

About The Position

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.

Requirements

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.
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
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.

Nice To Haves

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.

Responsibilities

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.
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.
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.
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.