Full Stack Software Engineer, Applied AI

About Wonderschool

Wonderschool builds software that helps small business owners earn more money. We started with childcare providers because it is a large, underserved market where technology can have an outsized impact on revenue. But the model scales: we are building a platform and a playbook that will expand into other verticals. We are heavy users of AI. OpenClaw agents run most of our operations: provider outreach, customer communications, enrollment workflows, compliance tasks. Non-engineers at Wonderschool spin up automations, cron jobs, and API workflows directly from Slack, without touching a line of code. We are now taking the next step: making AI agents reliable enough to build the product itself. Our team is small and moves fast. We value engineers who are obsessed with outcomes, not process.

The Vision

The North Star for this role: a system where a user signal such as a provider revenue dropping, an enrollment bottleneck, or a churn spike automatically triggers a chain of AI agents that writes the product requirements, designs the solution, builds the code, reviews it, and ships it. No human in the loop for the routine stuff. Humans define what matters, train the agents, and review edge cases. We are not there yet. You are the person who helps us get there, piece by piece.

About the role

You will define and evolve the technical foundation that enables fully autonomous AI agents to build and ship code in production. You will design the workflows, build the scaffolding, and own the reliability of the system that turns live signals into deployed features with minimal human intervention.

What you'll do

Own the AI Development Loop. Review and iterate on AI-generated code from tools such as Claude Code, OpenClaw, Codex, and Cursor, then feed that review back as training signals to improve the agents over time. Architect the codebase for AI legibility by enforcing clean data models, strong documentation, and deprecating legacy patterns that cause agents to fail. Build and maintain the automated product pipeline that handles signal detection, agent-generated requirements, AI-driven development, AI code review, and automated commits. Take ownership of diagnosing and fixing issues when agents break in production environments. Enable the Business, Not Just the Product. Build tools and workflow infrastructure that empower operations, sales, and customer success teams to operate the platform independently without filing engineering tickets. Translate ambiguous business needs into automated, reliable systems and help non-engineers understand possibilities so they can be executed. Ship Full-Stack Product. Build features across the frontend and backend using React and TypeScript on the front and Node.js or Elixir on the back, with Postgres as the relational database. Own the full lifecycle from requirements to production operation. Debug issues across the entire stack. Stay Close to What Is Live. Actively observe the production environment to analyze usage patterns, agent failures, edge cases, and provider behavior. This role requires a high degree of personal accountability for system health. When things are running well, that is because you have built the monitoring and alerting to catch problems early. Getting there takes commitment.

Requirements

You must possess 5 or more years of experience as a full stack engineer. You need hands-on experience with AI coding agents such as Claude Code, OpenClaw, Codex, or Cursor within a real development workflow. You should demonstrate strong product instincts, converting ambiguous user signals into concrete technical requirements without heavy product management support. You must show proficiency with React and TypeScript and at least one backend language such as Node.js, Elixir, Ruby on Rails, or similar technologies. You need experience working with Postgres or similar relational database systems. You must have a high ownership mentality and not wait to be told when something is broken. You are expected to communicate clearly, directly, and effectively in both written and verbal forms.

Preferred Qualifications

Experience building or operating agentic workflows in production. Experience designing feedback loops that improve AI output quality over time. Background at a startup or high-growth company. Experience with CI/CD, DevOps, or cloud infrastructure. Experience with REST or GraphQL API design.

Practical Notes

This is not a 9-to-5 role. At this stage, getting AI agents to ship reliable production code requires close observation of what is actually happening in the codebase. When the system is working well, that monitoring is lightweight and mostly automated. Ge