Staff Quality Automation Engineer
AI-infrastructure company producing memory-centric hardware, networking, and software for low-latency generative-AI inference in data centers.
Funding history
About d-Matrix
d-Matrix develops digital in-memory-compute technology and a full-stack inference platform comprising Corsair accelerators, JetStream networking accelerators, and Aviator software.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build and maintain shared automation, test frameworks, and harnesses for functional, integration, regression, and release testing. You will turn prototypes into reliable internal tools with clear interfaces, configuration, documentation, diagnostics, and error handling. You will integrate tools with CI, nightly, and release workflows, record reproducible test results, assess coverage and failures, and work with developers to verify fixes. You will also evaluate AI coding and workflow tools for quality-engineering use.
Requirements
- 5+ years of experience
- Strong software development skills, including coding, debugging, maintenance, design explanation, code review, and failure investigation
- Experience building shared test automation, frameworks, or engineering tools
- Experience turning prototypes or manual workflows into reliable tools
- Practical test engineering experience with requirements, boundary cases, negative cases, coverage, and reproducible experiments
- Experience with Linux, version control, code review, automated testing, and CI workflows
- Regular use of AI coding agents or AI workflows
- Experience guiding technical work across distributed teams through design and code reviews
Responsibilities
- Collaborate with Quality Engineering and Engineering to understand user needs, define scope, and prioritize work
- Build and maintain shared test automation, frameworks, and harnesses
- Turn scripts and prototypes into reusable tools with configuration, documentation, diagnostics, and error handling
- Integrate tools with CI, nightly, and release workflows
- Record builds, configurations, commands, inputs, and results to reproduce failures
- Support tool adoption through documentation, examples, and user feedback
- Assess test coverage, assertions, expected results, and negative cases
- Investigate failures and work with developers to verify fixes
- Evaluate AI coding agents and workflow tools for Quality Engineering work