- Location
- Austin, Texas, United States · published
- Workplace
- Onsite
- Type
- Full-time
- Department
- Operations
- Seniority
- Entry
- Source
- Workable
Description
Texas Sports Academy is a K-12 school designed for serious student-athletes who want both elite academics and high-level athletic development. Students cover 2x the material in just 2 hours a day, using the same 2-Hour Learning model as Alpha Schools. That frees up their entire afternoon for serious training, where they work alongside former pro and D1 athletes coaching them at the highest standard.
We're hiring an AI Operations Associate to work in person at our Austin office. You’ll work directly with the person who runs hiring for the academy and built our whole recruiting pipeline on AI tools, from candidate screening to Slack bots to KPI dashboards. You’ll do a huge variety of work: running Facebook ads, creating AI videos, building websites and automations, screening candidates, writing job posts, and whatever the academy needs next. All of it gets done in an AI-first way. It's an apprenticeship: you'll learn the tools on the job while producing real work from the start.
What You'll Do
- Wear Many Hats: No two weeks look the same. You might run Facebook ads, create AI videos, build automation,or ship an internal dashboard, then start on something new. If you want a job where you do a huge variety of work, this is it.
- Task Management: Track your own tasks and deadlines, keep the team updated on progress, and finish projects on time.
- Applied AI: You’ll get access to the world’s best AI models, video generation models, and agent harnesses like Claude Code and Codex, and you’ll learn which one fits each task so the work gets done faster and better.
- Web Development: Build and update websites and small internal tools with AI coding tools like Claude Code, Cursor, and Codex. You don’t need significant prior coding experience. The tools write most of the code, and you learn to direct them and check the work.
- Automation: Build automations and integrations that remove repetitive work for the team.
- Experimentation: Pitch your own ideas for what AI could do here, test them, and build the ones that work.