Founding Operations & AI Lead

This is a hybrid opportunity to lead Operations & AI performance in a well-funded stealth company experiencing more demand than they can handle.

The founder and CEO is one of the more widely known business leaders in the US, building AI agents that handle every part of how companies make money.

Working directly with the CEO, Head of Product, and advisors, in the immediate future you’d own customer onboarding & success, and lead improving the product by refining the underlying AI.

Long-term, you’d lead operations and customer success at scale.

Key Responsibilities:

Prompt Optimization & AI Enhancement

• Write, test, and refine AI prompts to maximize efficiency and response quality.
• Collaborate with product and engineering to optimize AI agent performance based on customer interactions.
• Develop a structured approach to prompt engineering and iteration, ensuring consistency and scalability.

Customer Onboarding & Internal Tools

• Own and streamline customer onboarding, ensuring a seamless experience using internal tools.
• Quickly integrate new customers into the platform by configuring workflows and prompts to meet their needs.
• Identify bottlenecks in onboarding and work with product to automate and improve the process.

Customer Success & Retention

• Ensure high customer satisfaction by proactively addressing issues and refining AI interactions.
• Act as the primary point of contact for customers, gathering feedback and surfacing insights to the product team.
• Develop scalable customer success strategies to improve retention and long-term adoption.

Operational Excellence & Automation

• Work with product and engineering to automate prompt management, onboarding workflows, and customer success processes.
• Establish repeatable and efficient operational frameworks to support company growth.
• Set up internal dashboards and reporting to track key success metrics for customer experience and AI performance.

AI Testing & Performance Optimization

• Design and execute structured tests to measure AI response quality, accuracy, and effectiveness.
• Develop benchmarking methods to track improvements in AI performance over time.
• Work with product and engineering to implement feedback loops that refine AI behavior based on real-world usage.
• Identify failure patterns and edge cases to improve AI consistency and reliability.
• Establish a scalable framework for ongoing AI testing, ensuring continuous improvement as the platform evolves.

Sponsorship is not available at this time.