Job Application for Head of AI Agent Systems at Wonderschool

About Wonderschool

Wonderschool builds software and systems that help businesses operate, grow, and generate revenue.

We started in childcare, where we provide a platform that helps providers manage enrollment, operations, compliance, and payments. We also partner with governments to run large-scale childcare programs.

We are a Series B company backed by Andreessen Horowitz, Goldman Sachs, Long Journey Ventures, and First Round Capital. The business is cash flow positive and expanding that position.

We are building a unified platform that combines marketplace, SaaS, and government infrastructure. We are expanding into adjacent verticals over time, including healthcare, microschools, and other service-based businesses.

A core part of our strategy is using AI to automate how work gets done across the company. This includes product development, operations, customer support, and go-to-market. We are also building systems to improve compliance, oversight, and fraud detection, particularly in government-funded programs.

We have already deployed a multi-agent system using OpenClaw and our internal Claude Code system. These agents operate across product, engineering, design, data, and operations. Parts of the system work today. Much of it is inconsistent, hard to measure, and not reliable enough for production use.

This role is responsible for fixing that and turning it into a system that drives revenue.

Position Summary

The Head of AI Agent Systems owns the design, performance, and evolution of Wonderschool’s multi-agent system.

This role is responsible for turning a partially working agent system into a production-grade platform that directly drives revenue by improving how we acquire customers, onboard them, operate their businesses, and iterate on product.

This is a hands-on role. You will work directly in the codebase, agent system, and infrastructure while leading a small team of engineers. You will be responsible for making the system work in practice and tying it to business outcomes.

This role reports directly to the CEO.

Responsibilities

Drive Revenue Through Agent Systems

Design and deploy agent-driven workflows that directly impact revenue generation
Improve conversion, onboarding speed, and provider revenue through automation
Partner with product and go-to-market to identify high-leverage revenue opportunities and implement them through agent systems
Use agents to accelerate experimentation on pricing, enrollment, and growth features
Tie agent performance to business outcomes such as revenue growth, conversion rates, and usage

Own Agent System Architecture and Performance

Own the architecture of the multi-agent system including OpenClaw, Claude Code, GBrain, and internal tooling
Improve agent output quality so outputs are usable without heavy human correction
Identify and fix system-level issues including poor outputs, coordination failures, memory loss, and context limitations
Design evaluation systems to measure success rates, failure modes, and reliability

Build a Reliable Multi-Agent Execution System

Redesign agent workflows so core processes execute reliably end-to-end
Ensure product development workflows from requirements through deploy can run through agents
Improve agent-to-agent coordination so tasks are completed without manual intervention
Introduce validation layers, retry logic, and clear ownership across workflows

Drive Adoption Across the Company

Enable engineering, product, design, go-to-market, and operations teams to use agents in their daily workflows
Define and enforce standards for how work is done using agents
Reduce reliance on manual processes by shifting execution to agent systems
Ensure systems are usable by non-engineers

Build Measurement and Feedback Loops

Implement system-wide reporting on agent performance
Track success rates, failure types, task completion, and human intervention
Use this data to continuously improve system performance
Create a system that improves over time rather than degrading

Lead and Scale the Team

Lead a small team of 2-3 engineers including DevOps
Hire and develop engineers who can build and operate agent systems
Maintain a high performance bar and clear accountability
Balance hands-on work with team leadership

Drive Business Impact

Increase provider revenue and platform usage through better systems
Improve speed of shipping features tied to revenue and growth
Automate workflows that reduce cost and increase margins
Support fraud detection and compliance systems that protect revenue and improve program integrity

What Success Looks Like (6-12 months)

Agents produce high-quality outputs with minimal human correction
All agents are tracked and measurable across success rate, failure modes, and usage
Teams across engineering, product, and operations use agents in daily workflows
Core workflows run reliably through agent systems
Agent systems are directly tied to measurable revenue outcomes including increased conversion, faster onboarding, and higher revenue per provider

Required Qualifications

Strong engineering background with experience building and shipping production systems
Experience working with AI systems, LLMs, or automation in a real environment
Experience debugging complex systems and improving reliability
Ability to work directly in code and system architecture
Experience building internal tools or developer systems is strongly preferred
Ability to operate in a fast-paced, high-ownership environment

Preferred Qualifications

Experience building or working with multi-agent systems
Experience with workflow automation or internal platforms
Experience working with regulated systems or compliance-heavy environments
Background as a founder or early engineer at a startup

What We Are Looking For

Someone who builds systems that work, not just prototypes
Someone who can take a messy system and make it reliable
Someone who connects technical systems to business outcomes and cares about revenue
Someone who moves quickly and focuses on outcomes
Someone who is comfortable working directly with leadership and making decisions

What This Role Is Not

Not a traditional Head of Engineering role
Not focused on managing large teams
Not a research or experimentation role

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Head of AI Agent Systems

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