Sr. AI Customer Success Manager
About The Position
The AI Customer Success Manager is an overlay enablement and adoption strategist working across regional Customer Success teams. As AI-powered products reach General Availability and sustained operations, this role helps customers achieve value, build trust, and maintain continuous usage. The manager serves as a trusted advisor, helping clients activate, integrate, and maximize value from QAD’s AI platform. Success is measured by AI product adoption, AI-specific net revenue retention, and AI customer referenceability. This remote role includes up to 25% regional travel. The manager supports customers and Customer Success Managers through AI product implementation and onboarding, delivers post-go-live training and enablement, monitors adoption metrics, and works with internal teams to address technical issues and improve products. The role also helps customers understand and reinvest capacity freed by AI, supports organizational changes in work practices, and leads adoption recovery when usage declines. QAD | Redzone provides an intelligent platform connecting people, processes, and data for manufacturing and supply chains. The company describes itself as virtual first, with employees primarily working from home and occasional travel to a physical office potentially required. QAD states its commitment to diversity, equity, inclusion, employee growth, and equal employment opportunity.
Requirements
- At least 5 years of experience in customer-facing or operational roles, such as Customer Success, Technical Account Management, Management Consulting, or Operations.
- Practical experience with manufacturing or supply chain workflows, such as sourcing, accounts payable/procurement, inventory management, or Sales Operations, alongside exposure to enterprise AI/ML platforms, developer tools, or business process automation.
- Solid understanding of strategic sourcing, Sales Operations, supply chain risk management, inventory optimization, and shop-floor or back-office productivity levers.
- Solid understanding of AI 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 complex technical AI processes into clear business value.
- Ability to adapt to shifting requirements in a fast-paced, high-growth startup environment.
- Ability to build customer trust and empathetically diffuse escalations.
- Bachelor’s degree in Business, Computer Science, Data Analytics, or a related field, or equivalent practical experience.
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 for their industry, data schemas, and domain terminology.
- Capture customer friction points and share them 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, PS-led implementations of AI-powered products as go-live milestones approach, supporting CSMs and customers through technical onboarding.
- Design and deliver post-go-live end-user training, tactical playbooks, customer office hours, and workflow integration sessions.
- Review customer handoff briefs to understand customer-specific details, edge cases, and operating realities before assuming operational ownership.
- Identify and escalate launches that fall below baseline metrics.
- Monitor AI product adoption metrics and work with Agent Ops when agent behavior issues are identified.
- Partner with Regional Customer Success Managers to maintain continuous usage and relationship health across 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.
- Work with customer executive sponsors and operational leaders to track capacity freed by AI agents and establish workflows to reinvest it in strategic projects.
- Guide customer teams from manual, reactive work toward proactive, exception-based decisions and strategic supplier or customer management.
- Lead adoption recovery when enablement challenges, low AI trust, or training gaps cause adoption to decline.
- Work with Product and Engineering to identify the causes of adoption declines using user feedback, performance scores, and usage data.
- Implement tailored training, workflow updates, and change-management initiatives, and measure outcomes at the 30-day checkpoint.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
