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About the Role

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.

Responsibilities

Build and ship product features across the full stack every week, with AI coding tools running alongside you.
Contribute to real LLM-powered product features: tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, and the evals behind them.
Work directly with the founders and senior engineers on scope and trade-offs, with no PM layer in between.
Pick up ownership of smaller systems end-to-end and grow into bigger ones.
Run your own AI coding workflow, prompts, subagents, custom tools, MCP servers, and get sharper at it every week.
Write evals and regression tests for AI features the same way you'd write unit tests for classical code.
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.

Skills

AI coding tools
LLM-powered product features
Tutoring agents
Parent-facing copilots
Coach-facing dashboards
Retrieval over student data
Evals
AI engineering
TypeScript
React
Node
Python
Postgres
AWS
GCP
Agent frameworks
LangGraph
CrewAI
Mastra
Vector search
RAG
Braintrust
LangSmith
Prompt caching
MCP servers
Structured output
Tool-use
Voice agents

Location

Austin, TX

Work Type

Full-time

Experience Level

Junior
0-2 years

Education Level

Bachelor's degree
Master's degree

About the Company

Texas Sports Academy runs a school focused on student records, academic mastery tracking, training data, parent portals, admissions, and AI-powered tools for guides and coaches.