Principal Program Manager - AI Excellence

Summary

The Principal Program Manager - AI Excellence role at CyberArk involves leading the strategic integration of AI-driven practices across the global Product and Technology organization. This position requires a deep understanding of cross-functional process optimization, organizational change, and emerging technologies. The role focuses on identifying high-impact AI use cases, removing adoption barriers, and integrating AI tools into the product development lifecycle. Key responsibilities include defining AI enablement strategies, identifying and scaling AI use cases, developing frameworks for assessing new tools, promoting AI-driven practices, collaborating with various teams to ensure responsible AI adoption, and establishing KPIs to measure AI’s impact on productivity and efficiency. The role reports to the VP of Operations for P&T.

CyberArk is hiring a Principal for AI Acceleration to lead the strategic adoption of AI-driven practices across our global Product and Technology (P&T) organization.

This new role is designed for an experienced operator and systems thinker who brings a deep understanding of cross-functional process optimization, organizational change, and the practical application of emerging technologies. As the AI Acceleration Principal, you will play a horizontal, enabling role—working across engineering, product, design, and operational functions to identify high-impact use cases, remove barriers to adoption, and embed AI tools and methodologies into the fabric of our product development lifecycle.

You will report directly to the VP of Operations for P&T and will act as a key force in shaping how AI enhances productivity, quality, and efficiency across the organization.

Key Responsibilities

Strategy & Planning:

• Define and drive a strategic roadmap for AI enablement in Product & Technology, aligned with business and operational goals.
• Stay current with AI trends and evaluate tools and technologies for potential adoption in enterprise SaaS development environments.

Enablement & Adoption

• Partner with cross-functional teams to identify, prioritize, and scale high-value AI use cases (e.g., AI-assisted documentation, code generation, test automation, support triaging, operational analytics).
• Facilitate proof-of-concept initiatives, assess outcomes, and create playbooks for wider rollout.
• Develop frameworks for assessing business impact and integration readiness of new tools.

Organizational Change & Collaboration

• Act as an internal champion and coach for AI-driven practices—building awareness, creating training pathways, and fostering a culture of experimentation.
• Collaborate with Security, Compliance, and Legal to ensure responsible and ethical AI adoption practices.
• Work with Data and IT teams to ensure required infrastructure and governance are in place for safe AI usage.

Metrics & Communication

• Establish KPIs to measure AI adoption, impact on productivity, and operational efficiency improvements.
• Communicate progress, learnings, and outcomes regularly to senior stakeholders across the organization.

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