Full-Time

Junior Software Engineer

AI-Forward

Updated on 8/1/2026

Texas Sports Academy

Texas Sports Academy

No salary listed

Austin, TX, USA

In Person

Category
Software Engineering (1)
Required Skills
LLM
Python
React.js
Software Testing
Postgres
RAG
TypeScript
AWS
LangGraph
Google Cloud Platform
Requirements
  • A bachelor's or master's degree in Computer Science, Engineering, Mathematics, or Physics.
  • Zero to two years of full-time engineering experience; strong internships, side projects, and shipped personal work count.
  • Daily, fluent use of AI coding tools such as Claude Code, Cursor, Codex, Windsurf, Aider, or an equivalent agent loop as the default way of writing software.
  • Comfort with a modern web stack including TypeScript, React, Node, Python, Postgres, and AWS or Google Cloud Platform.
  • Excellent written English.
  • Based in Austin, Texas.
Responsibilities
  • Build and ship product features across the full stack every week, with AI coding tools running alongside.
  • Contribute to real large language model-powered product features, including tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, and the evaluations behind them.
  • Work directly with the founders and senior engineers on scope and trade-offs.
  • Take ownership of smaller systems end-to-end and grow into larger systems.
  • Run an AI coding workflow using prompts, subagents, custom tools, and Model Context Protocol servers.
  • Write evaluations and regression tests for AI features in the same way unit tests are written for classical code.
  • Ship production code and AI features used by students, parents, and staff.
  • Own smaller systems and features end-to-end while ramping up.
  • Move features from idea to production quickly without breaking them.
  • Develop AI engineering skills alongside the senior team.
Desired Qualifications
  • At least one shipped LLM-powered project, school project, hackathon, or side project with an evaluation story.
  • Experience with agent frameworks such as LangGraph, CrewAI, Mastra, custom frameworks; vector search or retrieval-augmented generation; evaluation tools such as Braintrust, LangSmith, or custom systems; prompt caching; MCP servers; structured output or tool use; or voice agents.
  • A public GitHub profile or a personal AI project that can be tried.
  • A personal project built independently out of personal interest.
  • A background in education, educational technology, or sports.

Company Size

N/A

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A