Sr. AI Customer Success Manager

QAD

21h•Remote

About The Position

The AI Customer Success Manager is an overlay enablement and adoption strategist supporting regional Customer Success teams. As AI-powered products mature into General Availability and sustained operations, this role helps customers achieve value, build trust, and sustain product usage. The manager acts as a trusted advisor, helping clients activate, integrate, and maximize value from the AI platform. Success is measured by AI product adoption, AI-specific net revenue retention, and AI customer referenceability. The role supports AI customer onboarding and post-go-live adoption, provides end-user education, monitors usage and product metrics, and works with Customer Success, Product, Engineering, Support, Solutions Engineering, and Agent Operations to address issues and improve the platform. It also coaches customers on measuring capacity freed by AI agents and reinvesting it in strategic work, guides organizational and process changes, and leads recovery efforts when adoption falls. The position is remote in the UK or US, with up to 25% domestic travel and occasional international travel. Flexible hours may vary according to 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 using tools 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 in a fast-paced, high-growth startup environment with shifting requirements.
Ability to build customer trust and empathetically defuse escalations.
Practical experience with manufacturing or supply-chain workflows, such as sourcing, AP/procurement, inventory management, or Sales Operations.
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 hours that may vary day to day based on customer needs and milestones.
Willingness to travel up to 25% domestically for customer visits, industry conferences, and QAD meetings, and occasionally internationally.

Nice To Haves

Experience in manufacturing, supply chain, or enterprise SaaS environments.

Responsibilities

Coach users on AI value realization, workflow configuration, and effective prompt engineering.
Help customers configure AI for their industry, data schemas, and domain terminology.
Capture customer friction points and feedback to inform 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 regional Professional Services-led AI implementation projects as go-live milestones approach.
Support Customer Success Managers and customers through technical onboarding to reduce friction.
Design and deliver post-go-live end-user training, tactical playbooks, customer office hours, and workflow integration sessions.
Review handoff briefs to understand customer-specific nuances, edge cases, and operational realities before taking operational ownership.
Identify and escalate launches that fall below baseline metrics.
Develop expertise in AI product metrics and work with Agent Operations when issues with agent behavior are identified.
Partner with regional Customer Success Managers to maintain usage and relationship health across enterprise accounts.
Provide ongoing end-user guidance, tips, and workflow optimization to support long-term retention.
Capture ongoing 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 for reinvesting 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 adoption recovery strategies when enablement challenges, low AI trust, or training gaps cause adoption to decline.
Work with Product and Engineering to analyze user feedback, performance scores, and usage data to identify causes of declining adoption.
Deliver tailored training, workflow updates, and change-management initiatives, and measure their success at the 30-day checkpoint.