Sr. AI Customer Success Manager
About The Position
The Sr. AI Customer Success Manager is an overlay enablement and adoption strategist supporting regional Customer Success teams as AI products move into general availability and sustained operations. The role helps customers activate, integrate, and maximize value from the AI platform, building trust and ongoing usage. Success is measured through AI product adoption, AI-specific net revenue retention, and AI customer referenceability. This role supports customers across onboarding, go-live, and ongoing operations. It monitors adoption metrics, enables users through training and workflow guidance, collaborates with Customer Success Managers and technical teams, and feeds customer insights back to Product, Product Operations, and Engineering. It also coaches customer leaders on attributing and reinvesting capacity freed by AI agents, helps organizations shift toward proactive, exception-based work, and leads recovery strategies when adoption declines. The position is remote, with primary work performed from home and up to 25% regional travel. Occasional travel to a physical office may be required. Working hours are flexible and may vary day to day based on customer needs and milestones.
Requirements
- At least 5 years of experience in customer-facing or operational roles, such as Customer Success, Technical Account Management, Management Consulting, or Operations.
- Solid understanding of strategic sourcing, Sales Operations, supply chain risk management, inventory optimization, and shop-floor or back-office productivity levers.
- Solid understanding of artificial intelligence concepts, large language models, or data analytics infrastructure.
- Ability to interpret data trends, run basic data queries such as SQL or Excel, and build clear reporting frameworks.
- Ability to master a rapidly evolving technical product ecosystem.
- Knowledge of CRM software and Customer Success platforms.
- Exceptional presentation skills and ability to translate technical AI processes into clear business value.
- Adaptability to navigate shifting requirements in a fast-paced, high-growth startup environment.
- Ability to build customer trust and empathetically diffuse escalations.
- Practical experience with manufacturing or supply chain workflows, such as sourcing, AP/procurement, inventory management, or Sales Operations, alongside exposure to enterprise AI/ML platforms, developer tools, or business process automation.
- Bachelor's degree in Business, Computer Science, Data Analytics, or a related field, or equivalent practical experience.
- Flexible availability, with hours that may vary based on customer needs and milestones.
- Willingness to travel regionally up to 25%.
Nice To Haves
- Experience in manufacturing, supply chain, or enterprise SaaS environments.
Responsibilities
- Deliver coaching on AI value realization, workflow configuration, and effective prompt engineering.
- Help customers configure AI to reflect their industry, data schemas, and domain terminology.
- Capture customer friction points and feedback to influence the product roadmap.
- Partner with Solutions Engineers and Support to resolve complex technical issues and data anomalies.
- Document successful implementation patterns and develop playbooks for the Customer Success organization.
- Monitor PS-led implementation projects for AI-powered products as go-live milestones approach.
- Support CSMs and customers through technical onboarding to reduce friction at go-live.
- Design and deliver post-go-live end-user training, tactical playbooks, customer office hours, and workflow integration sessions.
- Review handoff briefs and understand customer nuances, edge cases, and field conditions before assuming operational ownership.
- Identify and escalate launches that fall below baseline metrics.
- Develop expertise in AI product metrics and work with Agent Ops when issues with agent behavior are identified.
- Partner with Regional CSMs to maintain usage and relationship health across established enterprise accounts.
- Provide ongoing end-user guidance, tips, and workflow optimization to support long-term retention.
- Capture customer feedback and usage signals and share them with Product Operations and Engineering.
- Coach customer executive sponsors and operational leaders to track capacity freed by AI agents and establish workflows to reinvest that time in strategic projects.
- Guide customer teams from manual, reactive tasks toward proactive, exception-based decision-making and strategic supplier or customer management.
- Lead recovery strategies when adoption drops because of enablement challenges, such as low AI trust or training gaps.
- Work with Product and Engineering to identify adoption root causes using user feedback, performance scores, and usage data.
- Roll out tailored training, workflow updates, and change management initiatives, and measure results at the 30-day checkpoint.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
