VP, Data/AI Engineering

VP, Data/AI Engineering

About SailPoint:

SailPoint is the leader in identity security for the cloud enterprise. Our identity security solutions secure and enable thousands of companies worldwide, giving our customers unmatched visibility into the entirety of their digital workforce, ensuring workers have the right access to do their job – no more, no less.

Built on a foundation of AI and ML, our Identity Security Cloud Platform, Atlas delivers the right level of access to the right identities and resources at the right time—matching the scale, velocity, and changing needs of today’s cloud-oriented, modern enterprise.

About the role:

SailPoint is on a fast-paced growth trajectory and seeks an innovative and hands-on leader to join their team as the VP, Data/AI Engineering, who will play a critical role in shaping and delivering on the future technology vision for the organization. Given the innovation agenda in the future combined with the complexity of the SailPoint platform and product portfolio, SailPoint requires a leader who has been at the cutting edge of technology with a deep architectural and technical understanding of handling massive amounts of real-time data.

The VP, Data/AI Engineering will be instrumental in building the best-in-class organization needed to support the businesses' goal of growing from $1B to $5B+ in ARR and be viewed as the clear #1 in identity, and top 3 companies in all of cybersecurity.

The VP, Data/AI Engineering will lead SailPoint’s global AI and machine learning initiatives, guiding distributed teams across multiple regions to build robust, scalable AI/ML solutions that power their products and critical business functions. The VP, Data/AI Engineering’s primary focus will be on backend and data-intensive areas, ensuring AI/ML systems are designed and deployed with the highest standards of technical excellence, performance, and scalability.

Reporting to the Head of Engineering as a member of the technical leadership for SailPoint, this role offers a unique opportunity to blend deep technical expertise with leadership skills, driving impactful change in a fast-paced and dynamic environment. The VP, Data/AI Engineering will be an inspiring people leader and a talent magnet that can attract, train, and retain best-in-class talent. They will be instrumental in creating a best-in-class team culture that aligns with SailPoint's "Four I" values.

Responsibilities:

• AI & ML Leadership: Shape the strategic vision and roadmap for AI and ML initiatives, ensuring global alignment with business goals and cutting-edge technology trends. Drive consistency and collaboration across geographically dispersed teams.
• Technical Oversight: Provide strong technical leadership in AI and ML engineering globally, particularly in areas like NLP, semantic search, summarization, and data-driven product development.
• System Architecture & Integration: Oversee the design and integration of complex AI and ML systems within their global software architecture. Ensure seamless interaction of these systems with other business-critical platforms and services across all regions.
• System Integrity & Security: Ensure the integrity, performance, and security of AI/ML systems globally. Implement best practices in data governance, model interpretability, and compliance with industry standards in all operational regions.
• Innovation & Continuous Improvement: Drive innovation in AI and ML practices on a global scale, continuously seeking opportunities to improve their technology stack, processes, and methodologies. Encourage innovative thinking and continuous improvement with a shared sense of purpose, ensuring a cohesive team environment across regions.
• MLOps & Data Platform Collaboration: Collaborate closely with MLOps, Platform Engineering, and Enterprise Data Platform teams to develop and optimize the global AI and ML infrastructure, including MLOps pipelines, data architecture, and model lifecycle management. Leverage modern cloud-based technologies and frameworks to ensure scalability, reliability, and efficiency across different regions.
• Cross-functional Collaboration: Collaborate closely with cross-functional teams, including product management, product engineering, and other business units, to align AI and ML initiatives with broader global company objectives.
• Team Leadership & Development: Lead and mentor a high-performing, globally distributed team of AI/ML engineers and data scientists. Foster a culture of innovation, collaboration, and continuous improvement, while ensuring effective communication and coordination across time zones.
• Talent Acquisition