Sr. AI Customer Success Manager
The AI Customer Success Manager operates as an overlay enablement and adoption strategist across regional Customer Success (CS) teams. As AI-powered products mature into General Availability (GA) and sustained operations, this role ensures customers rapidly achieve value, build trust, and drive continuous usage.
You will act as a trusted advisor to help clients activate, integrate, and maximize value from our AI platform. The ideal candidate possesses a unique blend of technical curiosity, consultative skills, and data literacy. Your primary metrics of success will be AI product adoption, AI-specific Net Revenue Retention (NRR), and AI customer referenceability.
Location: Remote with up to 25% Travel
Core Responsibilities
AI Adoption & Enablement
- AI Coaching: Deliver human enablement, teaching users best practices for AI value realization, including workflow configuration and effective prompt engineering.
- Data Contextualization: Assist clients in configuring the AI to properly reflect their specific industry, data schemas, and domain terminology.
Cross-Functional Collaboration
- Product Feedback: Act as the voice of the customer, capturing user friction points to directly influence the product roadmap.
- Technical Escalations: Partner with Solutions Engineers and Support to quickly resolve complex technical issues or data anomalies.
- Playbook Development: Document successful implementation patterns to scale best practices across the CS organization.
New Product Launch and Customer Onboarding
- Customer Onboarding: Monitor PS-led implementation projects for AI-powered products across the region as go-live milestones approach. Support CSMs and customers through technical onboarding processes to minimize friction points at this critical stage.
- Customer Enablement: Post Go-Live, design and deliver end-user training, tactical playbooks, customer office hours, and workflow integration sessions for regional CS teams and end-users.
- Phase Handoff to CS: Consume handoff briefs to understand customer nuances, edge cases, and field reality before taking operational ownership.
- Early Escalation: Identify and escalate launches falling below baseline metrics to prevent sustained adoption failure.
Sustained AI Operations
- Monitor Adoption Metrics: Develop deep expertise in available AI product metrics. Work with Agent Ops if the customer, the CSM and/or the Agent Ops team identifies issues with agent behavior.
- Ongoing Relationship & Usage Health: Partner with Regional Customer Success Managers (CSMs) to maintain continuous usage and relationship health across established enterprise accounts.
- In-Product & Operational Enablement: Continuously provide end-user guidance, tips, and workflow optimization to ensure long-term retention.
- Field Signal Feedback: Capture ongoing customer feedback and usage signals, feeding them back to Product Operations and Engr to continuously improve the core platform.
Strategic Value Attribution - Capacity Reallocation & Organizational Change
- Capacity Reinvestment Coaching: Partner with customer executive sponsors and operational leaders to track capacity freed by AI agents (e.g., 10,000+ hours annually across buying and AP teams) and establish structured workflows for reinvesting time into strategic projects.
- Behavioral & Process Mindset Shift: Guide customer teams away from manual, reactive tasks (e.g., chasing past-due POs, re-keying ERP data, manual quote entry) toward proactive, exception-based decision making and strategic supplier/customer management.
Adoption Rescue Playbook
- Ownership: Lead the recovery strategy when adoption drops driven by enablement challenges like low AI trust or training gaps.
- Identify Root Causes: Work with Product and Engineering to analyze user feedback, performance scores, and usage data to figure out why adoption dropped.
- Execution & Measurement: Roll out tailored training, workflow updates, and change management initiatives, measuring success at the 30-day checkpoint.