Togal.AI

Togal.AI

Customer Success Manager

United States

Sponsorship not specifiedDetected 47 days ago
Cloud PlatformsMachine LearningCRMSalesAccount ManagementCustomer SuccessCustomer SupportCommunicationCollaborationOrganizational Skills

About the role

  • Our solution uses advanced machine learning to automate traditionally time-consuming takeoff tasks, helping estimators work up to 80% faster while reducing costly errors.
  • Join us in revolutionizing pre-construction estimating with the power of AI!

Responsibilities

  • Customer Support and Success
  • Respond to support requests in a timely and professional manner
  • Maintain records of customer interactions and feedback
  • Monitor usage and identify churn risks early, addressing them with tailored support
  • Identify upsell and renewal opportunities and collaborate with the sales team to execute them

Requirements

  • Experience in customer success, account management, or a client-facing SaaS role
  • SaaS experience with a strong acumen for product knowledge
  • Ability to troubleshoot issues and explain technical concepts to non-technical users
  • Experience working with CRM or customer success platforms
  • Strong communication and relationship-building skills
  • Highly organized and proactive with a customer-first mindset
  • Located in CT/MT/PT time zone

Nice to have

  • Experience in construction tech or working with AEC clients is a plus
  • Opportunity to grow your career at a fast-paced AI startup
  • Collaborative and innovative work environment

Compensation

  • Base salary + Incentive Plan

Benefits

  • Health, dental, and vision insurance
  • Unlimited PTO and remote flexibility

Company info

  • Build strong relationships with customers, understanding their goals and ensuring they are met through the platform
  • Act as the primary point of contact for a portfolio of customers

Equal opportunity

  • We are an equal opportunity employer committed to building a diverse team.

This listing is sourced directly from Togal.AI's careers page and normalized into a canonical job model.