14 days ago
Belgrade, SerbiaStaff+
Responsibilities
- Partner with Quality Engineering and Engineering to understand user needs, define scope, prioritize work, and manage dependencies.
- Build and maintain shared automation, test frameworks, and harnesses for functional, integration, regression, and release testing across software and hardware configurations.
- Turn scripts and prototypes into reliable internal tools with clear interfaces, configuration, documentation, error handling, and diagnostics.
- Integrate tools with continuous integration, nightly, and release workflows, and record reproducible build, configuration, command, input, and result data.
- Support tool adoption through documentation, examples, user feedback, and independent usability checks.
- Assess test coverage, assertions, expected results, and negative cases; distinguish product defects from environment problems and unreliable tests.
- Work with developers to verify fixes and provide testing coverage while advancing shared automation.
- Evaluate AI coding agents and workflow tools, validate their outputs, and develop useful approaches into reusable QE capabilities.
Requirements
- 5+ years of experience.
- Strong software development skills, including writing, debugging, maintaining, reviewing, and explaining code and investigating failures beyond surface test results.
- Experience building shared test automation, frameworks, or engineering tools used repeatedly by others.
- Evidence of converting prototypes or manual workflows into reliable tools with configuration, failure handling, documentation, adoption, and maintenance.
- Practical test engineering experience covering requirements, boundary and negative cases, coverage, and failure investigation using code, logs, and reproducible experiments.
- Experience with Linux, version control, code review, automated tests, and CI workflows.
- Regular use of AI coding agents or AI workflows, with examples of implementation, iteration, and result validation.
- Experience guiding technical work across distributed teams through design and code reviews, understanding user needs, explaining tradeoffs, and working independently.
- Preferred experience includes systems software testing involving firmware, drivers, compilers, runtimes, distributed systems, or real devices.
- Preferred experience includes ML inference, model execution, numerical comparisons, quantization, performance benchmarks, test frameworks, CI pipelines, containers, reporting, lab automation, hardware-in-the-loop, multi-card or multi-node configurations, stability testing, or internal engineering products.
About d-Matrix
d-Matrix builds AI inference computing platforms for data centers, combining custom silicon with systems, networking, and software. Its flagship Corsair platform and JetStream fabric focus on low-latency, energy-efficient generative AI inference at scale. Founded in 2019 and headquartered in Santa Clara, California, the privately held company sells hardware with accompanying software to cloud providers and enterprises deploying large AI models.