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Sports Software Engineer Jobs in Austin, TX (NOW HIRING)

Work closely with and learn from our senior engineering team. * Contribute to the full software ... Monthly team get-togethers (Lunches, social events, sports outings, etc) Closinglock is an equal ...

Hybrid role, located in Austin, Texas Meet the Team Software is a team sport. The core of this team ... Your Impact As a Senior Software Engineer on one of our scrum teams, you'll own meaningful, highly ...

Meet the Team Software is a team sport. The core of this team was hand-picked from Austin's rich ... Your Impact As a Senior Software Engineer on one of our scrum teams, you'll own meaningful, highly ...

The Apple Services Engineering (ASE) team is one of the most exciting examples of Apple's long-held ... We are the people who power the App Store, Apple TV and Sports, Apple Music, Podcasts, and Books ...

We are the people who power the App Store, Apple TV and Sports, Apple Music, Podcasts, and Books ... entire software development lifecycle. Partnering closely with developers, system and site ...

Senior iOS Engineer, Ads

Austin, TX ยท On-site

$138K/yr

... in live sports on Apple TV. Everything we do is with the unwavering commitment to privacy you ... Your responsibilities will include all aspects of software engineering, from design and development ...

Senior iOS Engineer, Ads

Austin, TX ยท On-site

$138K/yr

... in live sports on Apple TV. Everything we do is with the unwavering commitment to privacy you ... Your responsibilities will include all aspects of software engineering, from design and development ...

Showing results 21-40

Sports Software Engineer information

See Austin, TX salary details

$62.9K

$146.2K

$203.7K

How much do sports software engineer jobs pay per year?

As of Sep 3, 2026, the average yearly pay for sports software engineer in Austin, TX is $146,227.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,900.00 and $171,500.00 per year, depending on experience, location, and employer.

What is a sports software engineer?

A Sports Software Engineer develops and maintains software solutions for the sports industry, such as performance analysis tools, game simulations, fan engagement platforms, and sports data analytics. They work with technologies like AI, machine learning, and real-time data processing to enhance athletic performance, optimize team strategies, or improve user experiences. This role requires strong programming skills, knowledge of sports-specific data, and the ability to collaborate with coaches, analysts, and other stakeholders.

What does a sports software engineer do?

As a Sports Software Engineer, you may work on projects like developing real-time analytics dashboards, building data pipelines for player and game statistics, or integrating wearable sensor data into coaching tools. Daily responsibilities often include collaborating with data scientists or sports analysts, designing user-friendly interfaces for coaches and athletes, and maintaining or optimizing existing systems. Many roles also involve ensuring accurate data capture, troubleshooting technical issues during live events, and customizing software for specific sports or teams. This work provides a dynamic environment where you see the direct impact of your code on athletic performance and team strategy.

What are the key skills and qualifications needed to thrive as a sports software engineer?

To thrive as a Sports Software Engineer, you need a strong foundation in software development, proficiency in programming languages such as Python, C++, or JavaScript, and a good understanding of data structures and algorithms, often supported by a degree in computer science or related fields. Familiarity with technologies like sports analytics platforms, sensor data integration, RESTful APIs, and version control systems, as well as experience with cloud services or machine learning, is highly valuable. Soft skills such as teamwork, strong communication abilities, and adaptability help you collaborate with coaches, analysts, and non-technical stakeholders. These combined skills ensure you can design and implement effective software solutions that drive performance insights and user engagement in the sports industry.

What are the most commonly searched types of Sports Software Engineer jobs in Austin, TX?

The most popular types of Sports Software Engineer jobs in Austin, TX are:

What are popular job titles related to Sports Software Engineer jobs in Austin, TX?

For Sports Software Engineer jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Sports Software Engineer jobs in Austin, TX look for?

The top searched job categories for Sports Software Engineer jobs in Austin, TX are:

What cities near Austin, TX are hiring for Sports Software Engineer jobs?

Cities near Austin, TX with the most Sports Software Engineer job openings:

Infographic showing various Sports Software Engineer job openings in Austin, TX as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $146,227 per year, or $70.3 per hour.

Junior Software Engineer (AI-Forward)

Texas Sports Academy Main

Austin, TX โ€ข On-site

Full-time

Re-posted 25 days ago


Job description

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.

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, 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.

Key Responsibilities
  • 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.
  • 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.
  • Based in Austin, TX.
Nice to Have
  • 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.