Build and ship full‑stack, LLM-powered features for an edtech product: tutoring agents, parent/coach copilots, retrieval over student data, and AI evals. Own small systems end-to-end, work closely with founders and senior engineers, ship weekly, and write evals and regression tests for AI features.
As a Junior Software Engineer with Texas Sports Academy, you'll help build the software that runs our school, student records, academic mastery tracking, training data, parent portals, admissions, and the AI-powered tools our guides and coaches use every day. This is an early-career, AI-forward seat. You'll work directly with the founders and senior engineers, ship code every week with AI in your loop, and grow into the LLM-powered features that make our school feel nothing like a traditional school.
What You Will Be Doing- Building and shipping product features across the full stack every week, with AI coding tools running alongside you.
- Contributing to real LLM-powered product features: tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, and the evals behind them.
- Working directly with the founders and senior engineers on scope and trade-offs, no PM layer in between.
- Picking up ownership of smaller systems end-to-end and growing into bigger ones.
- Running your own AI coding workflow, prompts, subagents, custom tools, MCP servers, and getting sharper at it every week.
- Writing evals and regression tests for AI features the same way you'd write unit tests for classical code.
- Pretending AI is optional. If you're not already coding with Claude Code, Cursor, Codex, or an equivalent agent loop, this role is not for you.
- Sitting in status meetings all day. Few meetings, more shipping.
- Working on a narrow slice of a giant codebase.
- Waiting around for tickets. You'll be in the room when we decide what to build.
- Ship production code and AI features that real students, parents, and staff rely on every day.
- Own smaller systems and features end-to-end as you ramp up.
- Move fast. Features go from idea to production in days, not quarters, without breaking things.
- Level up your AI-engineering chops alongside a senior team.
Requirements
- Bachelor's or master's degree in Computer Science, Engineering, Math, or Physics.
- Based in Austin, TX (or within commuting distance).
- 0 to 2 years of full-time engineering experience. Strong internships, side projects, and shipped personal work count.
- Daily, fluent use of AI coding tools (Claude Code, Cursor, Codex, Windsurf, Aider, or equivalent) as your default way of writing software.
- Comfortable in a modern web stack (TypeScript / React / Node or Python / Postgres / AWS or GCP).
- Excellent written English.
- At least one shipped LLM-powered project, school project, hackathon, or side project, with some kind of eval story.
- Agent frameworks (LangGraph, CrewAI, Mastra, custom), vector search / RAG, evals (Braintrust, LangSmith, custom), prompt caching, MCP servers, structured output / tool-use, or voice agents.
- Public GitHub or a personal AI project we can actually try.
- A personal project you built because you wanted to.
- Background in education, edtech, or sports.
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