VP, Customer Success (SaaS)

Location: United States

Salary: $245,000–$300,000 USD per year

Company

Enterprise SaaS company providing a cloud-native Context Intelligence Platform that harmonizes, unifies, and governs structured and unstructured data for analytics, operational systems, and AI applications.

What you will do

• Lead and scale a global Customer Success organization focused on retention, reduced churn, adoption, expansion, and customer advocacy.
• Define and operationalize value realization frameworks tied to measurable customer outcomes, including improved data quality, reduced operational friction, and faster time to insight.
• Ensure customers successfully adopt the platform as a mission-critical system of record and foundation for AI-driven enterprise functions.
• Design customer segmentation, account alignment, journey mapping, listening points, success metrics, and repeatable playbooks from pre-sales through implementation, go-live, and value realization.
• Build onboarding, ramping, continuous learning, and development programs for a global team.
• Represent the customer at the executive level and work with Product, Engineering, Go-To-Market, and Marketing teams on product improvements, customer councils, conferences, and thought leadership.

Requirements

• Relevant bachelor's degree; computer science or a related field is preferred.
• 15+ years of experience in highly regulated environments, including life sciences, healthcare, or financial services.
• Experience with SaaS, PaaS, IaaS, cloud, enterprise platforms, and master data management.
• Proven ability to lead, influence, negotiate, and build consensus across functions.
• Combined post-sale and sales experience, with a strong understanding of customer value drivers in recurring-revenue businesses.
• Excellent communication and presentation skills, analytical thinking, process orientation, and the ability to inspire and develop teams.

Culture & Benefits

• Customer-first culture focused on accountability, collaboration, continuous improvement, and knowledge sharing.
• Distributed workforce with flexible work arrangements.
• Opportunity to work on cloud-native data technology supporting enterprise digital transformation and AI use cases.
• Equal opportunity workplace with reasonable accommodation for applicants with disabilities.