zocdoc
AI Support Operations Manager
At a Glance
- Location
- New York, United States
- Experience
- 5–7 years
- Posted
- 2026-04-02T17:12:53-04:00
Key Requirements
Required Skills
Domain Knowledge
- Automation
- Engineering
Benefits & Perks
Soho location Unlimited Vacation 100% paid employee health ben
Requirements
5–7 years of experience, including 3–5 years in customer support operations, CX tooling, or similar roles
Hands-on experience implementing and optimizing AI-powered support tools (e.g., Forethought AI) and working within CRM platforms
Experience translating support processes and SOPs into scalable, system-driven workflows and automations
Experience partnering cross-functionally with Product, Engineering, CX, and Analytics to deliver operational solutions
Experience managing external vendors or AI platform partners and influencing product direction
A strong sense of ownership and bias to action, with a passion for applying AI and automation to improve customer and agent experiences
Compensation & Benefits
Flexible, hybrid work environment at our convenient Soho location
Unlimited Vacation
100% paid employee health benefit options (including medical, dental, and vision)
Commuter Benefits
401(k) with employer funded match
Corporate wellness program with Wellhub
Responsibilities
As an AI Support Operations Manager, you’ll play a meaningful role in evolving how we deliver customer support by using AI to create more efficient, high-quality experiences.
This is a first-of-its-kind role at Zocdoc, created at a pivotal moment in our growth as we invest in smarter support operations.
You’ll own how AI is designed and scaled across chat, voice, and email, helping automate repetitive work so our teams can focus on complex, human-centered interactions.
You’ll partner across teams to turn emerging AI capabilities into real, measurable outcomes.
Personally motivated by improving customer experiences through innovation and thoughtful application of AI
You genuinely love solving complex operational problems and turning ambiguity into scalable solutions