Remote AI Customer Success & Onboarding Expert

Synthires; United States; Remote; USD 76,000 - 110,000; Full time

Job summary

Cincinnatus LLC, acting as employer of record, is placing a remote Customer Support & Success Domain Expert with a leading AI lab. The role focuses on improving AI model performance through real-world operational expertise in support, onboarding, and success workflows.

You will work 40 hours per week on weekdays, leveraging tools like Intercom, HubSpot, Stripe and Metabase, and collaborate with research and engineering teams to refine evaluation rubrics and training data.

Qualifications

• Experience in customer support, customer success, or onboarding for business customers.
• Hands-on experience in ticket triage, escalation, churn/renewal, or onboarding.
• Daily experience with CRM/helpdesk tools (Intercom, HubSpot, Stripe, Metabase or equivalents).
• Ability to evaluate communications for authenticity and policy compliance.
• Career progression demonstrated.
• Availability for at least 40 hours per week on weekdays.
• Strong written communication and clear decision explanations.

Responsibilities

• Guide teams to improve AI support and onboarding workflows.
• Audit ticket triage, escalation, churn, renewals, onboarding, and billing.
• Design realistic support tasks from actual ticket data and constraints.
• Evaluate communications against rubrics and provide feedback.
• Collaborate with experts to ensure AI training data accuracy.

Skills

Customer support

Customer success

Technical onboarding

Policy compliance

Written communication

Tools

Intercom

HubSpot

Stripe

Metabase

Zendesk

Salesforce

Looker

Job description

Cincinnatus LLC, acting as employer of record, is placing a remote Customer Support & Success Domain Expert with a leading AI lab. The role focuses on improving AI model performance through real-world operational expertise in support, onboarding, and success workflows.

You will work 40 hours per week on weekdays, leveraging tools like Intercom, HubSpot, Stripe and Metabase, and collaborate with research and engineering teams to refine evaluation rubrics and training data.