Join the Edge AI team at Amazon as a Systems Development Engineer, where you will be responsible for the test and release infrastructure that validates custom AI accelerator silicon IP and ML inference software. This role requires a deep understanding of hardware IP and the ability to build scalable automation around it. You will design hardware-in-the-loop test frameworks and create new test processes from scratch. Your work will ensure continuous and reliable testing across Amazon's edge device portfolio.

• 3+ years of systems development experience
• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent work experience
• Proficiency in Python and at least one systems language (C or C++)
• Experience designing and executing hardware-in-the-loop or embedded system test automation
• Experience building CI/CD pipelines (Jenkins, CDK Pipelines, CodePipeline, or equivalent)
• Understanding of hardware IP concepts: registers, DMA, interrupts, memory-mapped I/O, or similar low-level system interfaces
• Experience with code coverage tooling, static analysis, or dynamic analysis integration in CI workflows
• Experience with AI/ML tools for engineering productivity (LLM-based automation, intelligent test selection, AI-assisted analysis workflows)
• Experience with embedded Linux build systems (Yocto/OpenEmbedded, Buildroot)
• Knowledge of neural network accelerator architectures, DMA engines, or custom silicon validation
• Experience with AWS infrastructure (Lambda, CDK, CloudWatch, S3, Step Functions)
• Familiarity with IOMMU, secure boot, ARM TrustZone, or hardware security concepts
• Experience creating test infrastructure from scratch for new hardware platforms
• Track record building scalable automation that other teams adopt
• Experience with SCA tools (Coverity, CodeQL, Klocwork) and DCA tools (ASAN, TSAN, Valgrind, fuzzing)
• Exposure to ML inference runtimes or neural network compilation

• Design, build, and maintain automated test systems that execute on physical AI accelerator silicon across device pools.
• Develop a deep understanding of AI accelerator hardware IP to write meaningful validation that exercises real silicon behavior.
• Define and implement new test methodologies and frameworks from the ground up.
• Apply AI fundamentals to enhance engineering effectiveness through automated log analysis and intelligent test selection.
• Implement and maintain code coverage, test coverage mapping, and static and dynamic code analysis integrated into the development workflow.
• Build and maintain release pipelines using AWS services and embedded build systems.
• Create dashboards and alerting for on-device inference metrics and investigate issues spanning hardware accelerator behavior.
• Collaborate with silicon validation, platform software, ML science, and QA teams to identify and close test gaps.

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.