Software Engineer in Test

The role is to establish testing framework for an AI audio and ad-tech platform, covering web, API, mobile, and IoT systems. The product is an in-store AI audio platform that streams dynamic music and targeted campaigns to physical retail spaces.

• 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

• 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
• 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

• 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