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Director of Quality Engineering

Job in Liberty Lake, Spokane County, Washington, 99019, USA
Listing for: Alarm.com
Full Time position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, IT QA Tester / Automation, Data Scientist
  • Quality Assurance - QA/QC
    Data Analyst, IT QA Tester / Automation
Salary/Wage Range or Industry Benchmark: 125000 - 150000 USD Yearly USD 125000.00 150000.00 YEAR
Job Description & How to Apply Below

Open Eye, the cloud video platform company, delivers intelligent video solutions that help organizations improve security, operations, and insight. Our platform combines cloud-managed video, edge-based systems, and AI-driven analytics to support video security, business intelligence, and loss prevention.

Open Eye is committed to developing an easy-to-use, comprehensive video management system backed by Heroic Customer Service® and support. Our on-site and cloud-based products are used in schools, hospitals, banks, retail environments, and other facilities around the world. Open Eye’s solutions are available globally through a trusted network of certified service providers. Open Eye is a subsidiary of  Learn more at

Job Summary

Open Eye is seeking an experienced Director of Quality Engineering to lead our quality organization within the Software Engineering department. This role is responsible for defining, executing, and evolving quality strategy across the platform while leading a high-performance organization that delivers reliable, scalable, and customer-focused software.

Role and Responsibilities Quality Strategy and Leadership
  • Establish and communicate a comprehensive quality strategy and vision aligned with company objectives and product roadmaps.
  • Own quality outcomes across the platform, including cloud services, edge‑based software, mobile applications, analytics and AI capabilities, and hardware integration.
  • Represent quality engineering in executive discussions, providing transparent reporting on product readiness, risks, and trade‑offs.
  • Establish frameworks for balancing speed and quality, enabling informed decision‑making on release timing and scope.
  • Increase organization‑wide transparency into quality strategy, test plans, and automation priorities so engineering and product leaders have consistent visibility into how quality is achieved across major initiatives.
  • Establish clear, consistent quality visibility standards that define how test plans, coverage, and quality signals are communicated at the feature, system, and release levels.
Organizational Leadership and Talent Development
  • Lead, develop, and mentor managers and teams across SQA, test automation, and release management functions.
  • Recruit, evaluate, and develop top talent to build and sustain world‑class quality engineering capabilities.
  • Oversee capability and capacity planning to ensure teams are appropriately staffed, skilled, and resourced to support current and future initiatives.
  • Foster a culture of accountability, collaboration, and continuous improvement within the quality organization.
Quality Engineering Practices and Automation
  • Define and evolve quality standards, methodologies, and best practices that drive predictable, high‑quality product releases.
  • Champion modern testing approaches, tools, and automation frameworks to improve coverage, efficiency, and signal.
  • Drive continuous improvement initiatives that reduce defects, improve reliability, and increase delivery confidence.
  • Establish and track metrics and KPIs to measure testing effectiveness, release readiness, and customer impact.
  • Translate testing results and automation outcomes into clear, actionable quality signals that support faster, more confident engineering and release decisions.
AI‑Enabled Quality Engineering
  • Serve as a technical and strategic leader for the responsible integration of AI into quality engineering workflows.
  • Drive the responsible adoption of AI-assisted testing, automation, defect analysis, and quality analytics to improve efficiency and decision-making.
  • Strengthen quality practices for analytics and AI-driven capabilities, with a focus on accuracy, reliability, and customer trust, and ensure validation approaches are reflected in test strategies, release readiness, and quality signals.
Release Readiness and Delivery
  • Own quality readiness for releases through close cross-functional collaboration and clear accountability for release risk and readiness.
  • Drive release planning and execution from a quality perspective, ensuring clear communication of quality status and risks.
  • Drive the evolution of CI/CD pipelines to ensure automated testing and quality…
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