Enterprise Customer Success Manager

Transcend is a company that focuses on building the compliance layer for customer data, enabling responsible AI adoption. They are seeking an experienced Enterprise Customer Success Manager to drive transformation within strategic customer partnerships and guide Fortune 500 leaders in building an AI-ready data foundation.

Responsibilities:

• Own the post-implementation experience for up to 65 accounts, guiding customers to leverage Transcend to unblock and accelerate their AI initiatives
• Proactively identify opportunities for customers to scale and influence decision-making at the executive level to consistently exceed retention and expansion targets
• Act as a strategic advisor to IT, Digital, and Compliance teams, supporting maturity curve progression with minimal oversight
• Use data-driven insights to prove how Transcend reduces technical debt and accelerates time-to-market for digital and AI programs
• Lead Business Reviews for C-suite stakeholders, translating complex technical “guardrails” into business growth and trust-building narratives

Requirements:

• Enterprise Mastery: 3+ years in Enterprise CS or a strategic consultancy function for F500 customers, with a proven record of navigating complex technical partnerships
• Autonomy & Mastery: Exceptional self-starter capability; you identify gaps in the customer journey or internal processes and can determine how to tackle new initiatives with minimal oversight
• Strategic Storytelling: Ability to articulate Transcend's value not just as 'compliance', but as the engine that enables responsible AI and personalized customer experiences
• Technical Intelligence: Ability to master a deep technical stack to strategically advise stakeholders through their data journey
• Async & Remote Efficacy: Expert-level ability to communicate clearly via writing, recorded demos, and documentation to drive results across distributed teams
• Agility & Grit: Comfort with the ambiguity of a startup; you are resilient, proactive, and capable of high-velocity execution
• AI/Data Engineering Context: Familiarity with how enterprises build AI pipelines or manage large-scale data warehouses (Snowflakes, Databricks, etc.)