Build and ship full-stack software and LLM-powered features for student records, tutoring, parent portals, coaching dashboards, and school operations. The role includes end-to-end ownership of smaller systems, AI-assisted development, prompt and agent workflows, retrieval over student data, evaluation design, and regression testing. Candidates collaborate directly with founders and senior engineers in a fast-moving Austin-based environment.
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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Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
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