Quality Assurance Intelligence Intern
Explicitly mentions vibe coding, prompt engineering, and daily use of AI coding assistants/LLMs for AI-augmented QA and rapid prototyping.
About the Role
An internship focused on building production-grade QA automation and AI-enabled testing solutions for sports technology using Python and modern AI tooling. The role emphasizes AI-assisted development, prompt engineering, automated test creation, and collaboration across global teams to deliver reliable, testable systems for real sports workflows.
Job Description
Role
Quality Assurance Intelligence Intern working on production-grade projects that combine Python, AI tooling, and automation to deliver reliable, testable solutions for sports-technology workflows. The role emphasizes AI-assisted development practices, prompt engineering, and end-to-end traceability in QA automation.
Key Responsibilities
- Develop automated, testable solutions from specifications, requirements, and acceptance criteria.
- Work with AI coding assistants (LLMs, copilots, prompt workflows) as daily development tools to accelerate QA engineering.
- Participate in AI-driven prototyping, experimentation, and rapid iteration while maintaining precision and traceability.
- Collaborate with global, cross-functional teams to integrate solutions into real sports workflows.
- Contribute to AI-enabled use cases and participate in technical discussions, design reviews, and problem-solving sessions.
Requirements
- Strong Python programming fundamentals.
- Enthusiasm for AI-assisted development and modern engineering workflows.
- Interest in prompt engineering, vibe coding, and AI-augmented problem solving.
- Detail-driven mindset with care for correctness and edge cases.
- Comfort working from specifications, requirements, and structured tasks.
- Passion for sports (playing, watching, analyzing, or building systems around them).
- Fast learner with ability to master new tools and frameworks.
- Clear communicator and collaborative team player, comfortable in global teams.
Desired Qualifications
- Familiarity with AI/ML frameworks such as PyTorch or TensorFlow and Model Context Protocol (MCP).
- Familiarity with Agentic AI design patterns for goal-driven systems.
- Experience or familiarity with AWS, Argo CD for CI/CD pipelines, and Microservices Architecture (MSA).
- Side projects involving sports data, player tracking, computer vision, or match insights.
- Experience using Git, APIs, or QA tooling.
- Knowledge of data visualization or event recognition in sports.
Benefits
- Mental Health Days Off
- No Meeting Fridays
- Flexible working schedules
- 2 days of Volunteering Time Off
- Employee Resource Groups and diversity, equity, and inclusion initiatives