Technical skills
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