Director of Software Quality Engineering

d-Matrix; United States; Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Equity

Health care

Flexible time-off

Paid paternity leave

401k retirement plan

Remote & hybrid working model

On-site fitness center

Free food and snacks

Peer coaching & development

Team-building activities

Happy hours

Job summary

d-Matrix in the United States seeks a Director of Software Quality Engineering to lead QA across firmware, compilers, runtimes, and inference‑serving software. You will define vision, test architecture, and automation strategy, while leading day‑to‑day execution and coaching the team.

First-year priorities include assessing current processes, building a practical roadmap, and expanding automation and AI-assisted practices to handle growing product complexity.

Qualifications

• Systems software testing experience across firmware, compilers, runtimes, drivers, distributed systems.
• Strong programming ability in Python and/or C++, including building test frameworks and reviewing test code.
• Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
• Experience evaluating AI-assisted engineering workflows and judging whether AI-generated tests verify intended behavior.
• Experience setting quality strategy and test architecture while leading daily delivery and developing a software quality team.
• Familiarity with inference-serving software and relevant performance benchmarks.
• Experience with Kubernetes-based test environments.
• Experience with hardware-in-the-loop testing and lab automation.
• Experience managing open-source license compliance.

Responsibilities

• Define the quality strategy, technical roadmap, and test architecture across firmware, compiler, runtime, and inference serving.
• Build reusable test frameworks and automated functional, integration, and end-to-end coverage across hardware and software.
• Lead automation strategy and day-to-day execution for the Software Quality Engineering team.
• Stay hands-on to review framework code, investigate complex failures, and guide technical decisions.
• Develop continuous soak testing to assess long-run stability and generate useful failure evidence.
• Coordinate open-source and proprietary license compliance with Legal and other stakeholders.
• Coach and develop the software quality engineering team.

Skills

Python

C++

Test frameworks

Code review

AI-assisted testing

Education

Bachelor’s degree in CS/engineering or related field

Tools

Kubernetes

Job description

• The Director, Software Quality Engineering leads quality across our firmware, compiler, runtime, and inference-serving software
• You will set the vision, define the test architecture, and lead both automation strategy and day-to-day execution for the Software Quality Engineering team
• Your first priority will be to assess our current processes, test content, tools, and frameworks. Create the practical roadmap while keeping current qualification work on schedule and developing the engineers who own it
• Automation and AI-assisted engineering are central to this role. Build on the foundation and extend the team’s capacity to meet growing product and release complexity through automation, reusable tooling, and AI-assisted practices
• You will stay hands‑on enough to review framework code, investigate complex failures, and guide technical decisions
• Our work spans numerical accuracy, performance, and stability on evolving hardware and software
• Because test capacity is finite, you will make coverage decisions and help the team use evidence to distinguish product defects, infrastructure problems, and unreliable tests
• You will also lead the company’s open‑source and proprietary software license compliance program (inbound and outbound) and coordinate the company’s AI use policy, working closely with Legal and other stakeholders
• Define the quality strategy, technical roadmap, and test architecture across firmware, compiler, runtime, and inference serving
• Build reusable test frameworks and automated functional, integration, and end‑to‑end coverage, with deliberate choices about what runs on available hardware and when
• Develop continuous soak testing to assess long‑run stability and produce useful failure evidence
• Establish numerical comparison and tolerance policies with engineering owners, and detect performance regressions against reliable baselines
• Define measurable QA readiness criteria and quality gates. Qualify the exact release candidate, including targeted customer fixes, and communicate results, gaps, and risks clearly
• Improve defect triage and turn lessons from customer‑reported defects into better coverage and engineering practices
• Evaluate and adopt AI‑assisted test generation, triage, and failure clustering where they deliver measurable benefits
• Establish and maintain processes for open‑source and proprietary software license compliance, including inbound and outbound obligations, in partnership with Legal
• Coordinate implementation and ongoing review of the company’s AI use policy with legal, security, and engineering leadership
• Coach and develop the software quality engineering team
• First‑Year Objectives (proposed):
• Establish a baseline of human effort in test preparation, execution, triage, and maintenance. Measurably reduce repetitive work on comparable workloads while preserving or improving coverage and defect detection
• Evaluate AI‑assisted testing on representative work and demonstrate gains in time to actionable results or engineering effort, including human review and maintenance costs
• Put documented numerical‑tolerance policies and performance‑regression gates into use with engineering owners so that agreed violations block progression and authorized exceptions are recorded
• Deliver an actionable quality roadmap, clear operating ownership, and shared knowledge so that critical workflows do not depend on any one person
• Specific targets and measurement windows will be agreed after the baseline is established

Benefits

• Equity
• Health care
• Flexible time‑off
• Paid paternity leave
• 401k retirement plan
• Remote & hybrid working model
• Work with world‑leading engineers and researchers
• Happy hours
• Team‑building activities
• On‑site fitness center
• Free food and snacks
• Peer coaching & development

Systems software testing experience in firmware, compilers, runtimes, drivers, distributed systems, or comparable software, including hardware/software integration with real devicesStrong programming ability in Python and/or C++, including building test frameworks and reviewing test codeBachelor’s degree in computer science, engineering, or a related field, or equivalent practical experienceAbility to evaluate AI‑assisted engineering workflows and judge whether AI‑generated tests verify intended behavior rather than merely passSound judgment about coverage, risk, and metrics, and the ability to work credibly with developers and communicate clear quality assessmentsExperience setting quality strategy and test architecture while leading daily delivery and developing a software quality or test engineering teamExperience designing test coverage under resource constraints, integrating tests into CI, and defining promotion and release gatesKnowledge of machine learning or inference, including quantization, numerics, and model accuracy evaluationFamiliarity with inference‑serving software and relevant performance benchmarksExperience with Kubernetes‑based test environmentsExperience with hardware‑in‑the‑loop testing, device farms, or lab automationExperience managing open‑source license compliance