Texas Sports Academy Main

Software Engineer

🇬🇧 Remote, GB Remote IT Full time Senior Posted May 1, 2026
LocationRemote, GB
WorkplaceRemote
EmploymentFull time
SenioritySenior
CategoryIT
IT CategoryFull Stack Engineer
LanguageEnglish
PostedMay 1, 2026
Last verifiedMay 8, 2026

Software Engineer (AI-Forward)

As a Software Engineer with Texas Sports Academy, you play a key role in building 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 a senior, AI-forward seat. You work directly with the founders, ship code every week with AI in your loop, and own the LLM-powered features that make our school feel nothing like a traditional school.

What you will be doing

  • Designing, building, and shipping product features across the full stack every week, with AI coding tools running alongside you.
  • Building real LLM-powered product features: tutoring agents, parent-facing copilots, coach-facing dashboards, retrieval over student data, evals for every one of them.
  • Working directly with the founders on scope, architecture, and trade-offs — no PM layer in between.
  • Owning the reliability, security, and cost of both classical systems and LLM pipelines.
  • Running your own AI coding workflow — prompts, subagents, custom tools, MCP servers — and raising the bar on how the whole team uses AI.
  • Writing evals and regression tests for AI features the same way you'd write unit tests for classical code.

What you will NOT be doing

  • Pretending AI is optional — if you're not already coding with Claude Code, Cursor, Codex, or an equivalent agent loop every day, this role is not for you.
  • Writing tickets for junior engineers to implement.
  • Sitting in status meetings all day — few meetings, more shipping.
  • Working on a narrow slice of a giant codebase.

Key responsibilities

  • Ship production code and AI features real students, parents, and staff rely on every day.
  • Own at least one major system end-to-end.
  • Move fast — features go from idea to production in days, not quarters — without breaking things.
  • Raise the AI-engineering bar as the team grows.

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