Software Development Engineer - Test Automation, Amazon Camera Sdk

Amazon Amazon · Big Tech · Gdansk, Poland · Software Development

Software Development Engineer in Test focused on AI-enhanced automation for camera SDKs, including audio/video pipelines, secure boot, and hardware abstraction layers, aiming to improve test coverage, reduce execution time, and enhance defect detection.

What you'd actually do

  1. Leverage AI and machine learning to evolve automated test frameworks for embedded systems and camera products
  2. Design and implement intelligent test automation for audio/video pipelines and board support packages
  3. Develop AI-driven testing solutions for secure boot implementations and hardware abstraction layers
  4. Apply AI techniques to enhance test coverage, reduce execution time, and improve defect detection across multi-platform embedded devices
  5. Create and execute data-driven test strategies and intelligent test case generation

Skills

Required

  • Experience integrating AI/ML technologies into test automation frameworks and processes
  • Strong programming skills (Python preferred) with experience in AI/ML libraries and frameworks
  • Experience in developing automated test frameworks for embedded systems and hardware-in-the-loop testing
  • Experience with computer vision, image processing, and video analytics for device validation
  • Experience executing test strategies, test plans and test cases in embedded device environments
  • Bachelor's Degree in Computer Science, Engineering, or related technical field

Nice to have

  • Experience with embedded device communication protocols (serial, BLE, network protocols)
  • Experience with multi-platform embedded testing (ARM, RISC-V architectures)
  • Knowledge of real-time systems testing and RTOS environments
  • Experience with AWS services integration and cloud-based testing infrastructure
  • Experience with performance profiling, power consumption analysis, and hardware debugging tools
  • Strong verbal and written communication skills with ability to work effectively across technical teams
  • CI/CD pipelines for device testing
  • Integrating test results with dashboards or monitoring systems

What the JD emphasized

  • AI/ML technologies into test automation frameworks and processes
  • AI/ML libraries and frameworks
  • computer vision, image processing, and video analytics for device validation

Other signals

  • AI-enhanced automation
  • AI-driven testing solutions
  • Apply AI techniques to enhance test coverage
  • Drive innovation in testing processes through AI integration