Inworld Ai
Head of Customer Success & Account Management - USA
Mountain View, California, USA, Remote. Posted a month ago
The role
You will build and lead the post-sales function, owning the customer lifecycle from onboarding to renewals and expansion. You will act as a player-coach, managing strategic accounts while building the team, operating model, and playbook.
What you will do
- Own gross and net revenue retention, renewal performance and expansion pipeline.
- Build a lifecycle from onboarding through adoption and value realization.
- Personally own highest-value and most complex accounts.
- Build multi-threaded relationships across technical, business and executive stakeholders.
- Define customer segmentation, coverage, service levels and division of responsibilities.
- Create repeatable playbooks that scale.
- Own the post-sales stack and reporting layer.
- Use AI agents and automation for account research and customer engagement.
- Partner with Sales, Product, Engineering and Support.
- Manage strategic accounts while recruiting, ramping and coaching first hires.
Required qualifications
- 7+ years in customer success, account management or post-sales
- 3+ years leading and hiring teams
- Track record of building or scaling a post-sales motion at a high-growth startup
- Experience owning a renewal and expansion number
- Deep experience managing strategic enterprise customers
- Comfort with highly technical products and technical buyers
- Hands-on command of modern CRM and customer success tooling
- Ability to hire, ramp and retain strong Customer Success and Account Management talent
- Ability to operate independently and thrive in ambiguity
- Exceptional written and verbal communication skills
Nice to have
- AI-native, using agents, automation and customer signals to identify risk, accelerate value realization and scale high-touch engagement
Benefits
- benefits
About the company
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. They build first-party speech models, serve LLMs, and run the inference behind modular APIs.