Customer Success Manager

Crusoe · Data AI · San Francisco, CA - US · Cloud Go-To-Market (GTM)

This role is for a Customer Success Manager at an AI infrastructure company. The primary focus is on managing customer relationships, providing technical guidance on cloud-based AI and ML solutions, monitoring performance, and resolving issues to ensure clients maximize value from the company's offerings. While the company is AI-focused, the role itself is customer-facing and does not involve building or directly working with AI models.

What you'd actually do

  1. Develop and maintain strong customer relationships, understanding their business needs and technical requirements.
  2. Provide technical guidance and support to customers in the implementation and optimization of our cloud-based AI and ML solutions including Kubernetes solutions.
  3. Conduct regular reviews and report on customer progress, ensuring the achievement of key performance indicators and return on investment.
  4. Stay up-to-date with industry trends, technical advancements, and regulatory changes to provide strategic advice to clients.
  5. Deliver training sessions and workshops to customers on the use and benefits of our products and services.

Skills

Required

  • Customer Relationship Management
  • Technical Guidance and Support
  • Performance Monitoring and Reporting
  • Industry and Technical Awareness
  • Customer Training
  • Issue Resolution
  • Bachelor’s degree in Business, Engineering, or a related field
  • Proven experience in customer success, technical account management, or a similar role in a technology-driven environment
  • Understanding of computing platforms, AI, and ML technologies
  • Ability to communicate complex concepts in simple terms
  • Strong interpersonal, communication, and presentation skills
  • Demonstrated ability to build relationships at all levels within an organization
  • Comfortable working in a fast-paced environment with ambiguous and/or iterative fact-sets

What the JD emphasized

  • strong technical understanding of cloud computing, AI, and ML
  • maximize the value of our solutions
  • achieve their business and sustainability goals
  • technical guidance and support
  • optimization of our cloud-based AI and ML solutions
  • key performance indicators
  • technical advancements
  • strategic advice
  • use and benefits of our products and services
  • technical proficiency
  • complex concepts in simple terms