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 architectureāspanning 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 Youāll Be Doing
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Establish the release gatekeeping strategy to independently approve or block production deployments across all platforms
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Convert manual hardware and software validation rules into automated regression suites using Claude Code
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Engineer end-to-end UI automation across four web applications using modern execution frameworks like Playwright
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Develop API integration tests validating real-time ad serving, playlist generation, and transactional event reporting
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Expand Docker Compose test environments to automate real-time streaming validation for Raspberry Pi edge devices
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Conduct physical edge-device testing to verify hardware power-loss recovery, local caching, and ad-insertion timing
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Author structured, edge-case-driven test documentation and step-by-step verification protocols in Notion
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Trace system failures directly through server logs, SSH sessions, and CLI diagnostics to deliver isolated bug reports
What We Expect
Must-have
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Computer Science degree or equivalent demonstrated depth through complex side projects, hardware builds, or competitive programming
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Advanced command-line proficiency (Linux CLI, SSH, process management, shell scripting, log analysis)
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Solid comprehension of distributed web architecture, API contracts, client-server interactions, and database behavior
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High degree of autonomy with a natural tendency toward systematic edge-case discovery
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Fluent spoken and written English with overlap for UTC+2 working hours
Nice-to-have
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Hands-on experience with AI -assisted software generation (Claude Code, Cursor)
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Exposure to embedded Linux, Raspberry Pi, or home-lab infrastructure
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Familiarity with test frameworks such as Pytest, Playwright, Vitest, or Cypress
Why This Role Is Worth Your Time
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Full authority over the release decision pipelineāyour sign-off directly controls what goes to production
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Early adoption of modern AI -first engineering workflows where test generation is built via AI pair-programming tools
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Direct ownership over end-to-end software and hardware execution loops, giving you broad operational reach across web, API, mobile, and IoT systems
