The Role
You will take complete ownership of quality across an ecosystem that serves real-time retail audio, ad campaigns, and IoT hardware streams daily. The core technical challenge is ensuring absolute reliability across a fragmented architecture—spanning four web apps, Python services, edge devices, and mobile platforms. You will establish the testing framework from scratch, migrating manual verification into AI-assisted test automation that dictates production releases.
About the Product
The product is an in-store AI audio and ad-tech platform that streams dynamic music, live announcements, and location-targeted campaigns to physical retail spaces. It runs on a distributed architecture handling multi-tenant web portals, complex ad-auction engines, mobile interfaces, and custom hardware playback devices operating in low-reliability network environments.
Technology Stack:The backend is built in Python, while the web interfaces use React and TypeScript alongside a React Native mobile player. Infrastructure and edge environments rely on Raspberry Pi running embedded Linux, orchestrated via Docker Compose, git, and GitHub Actions for CI/CD. Test engineering leverages Claude Code and Cursor for AI-generated automation across Playwright, Pytest, and custom CLI/Bash tooling.
What You’ll Be Doing
Establish the release gatekeeping strategy to independently approve or block production deployments across all platforms
Convert manual hardware and software validation rules into automated regression suites using Claude Code
Engineer end-to-end UI automation across four web applications using modern execution frameworks like Playwright
Develop API integration tests validating real-time ad serving, playlist generation, and transactional event reporting
Expand Docker Compose test environments to automate real-time streaming validation for Raspberry Pi edge devices
Conduct physical edge-device testing to verify hardware power-loss recovery, local caching, and ad-insertion timing
Author structured, edge-case-driven test documentation and step-by-step verification protocols in Notion
Trace system failures directly through server logs, SSH sessions, and CLI diagnostics to deliver isolated bug reports
What We Expect
Must-have
Computer Science degree or equivalent demonstrated depth through complex side projects, hardware builds, or competitive programming
Advanced command-line proficiency (Linux CLI, SSH, process management, shell scripting, log analysis)
Solid comprehension of distributed web architecture, API contracts, client-server interactions, and database behavior
High degree of autonomy with a natural tendency toward systematic edge-case discovery
Fluent spoken and written English with overlap for UTC+2 working hours
Nice-to-have
Hands-on experience with AI-assisted software generation (Claude Code, Cursor)
Exposure to embedded Linux, Raspberry Pi, or home-lab infrastructure
Familiarity with test frameworks such as Pytest, Playwright, Vitest, or Cypress
Why This Role Is Worth Your Time
Full authority over the release decision pipeline—your sign-off directly controls what goes to production
Early adoption of modern AI-first engineering workflows where test generation is built via AI pair-programming tools
Direct ownership over end-to-end software and hardware execution loops, giving you broad operational reach across web, API, mobile, and IoT systems
