Ziing was founded in Canada in 2018 by supply chain and technology experts. We think of mobility as a breeding ground for collective change. We saw an prospect to be the first logistics company that didn’t just integrate digital technology into our operations—we founded our entire business upon it. Harnessing the power of data, integrated systems, clean technology, and AI-driven automation, we help our clients deliver on their promise of excellent customer service. At

Ziing , we are setting new standards with our transformative enterprise platform that builds and integrates web, iOS, and Android applications. Our approach combines the forefront of modern technologies, including generative AI and comprehensive Microsoft ecosystems, within a culture that merges the agility of a Startup with the reliability of Enterprise frameworks. We’re committed to innovation, smart risk-taking, and impactful technology solutions. Our core values of

humble, hungry

and

mindful

are at the forefront of everything we do. Director, Quality Engineering

About the Opportunity

We are looking for a Director of Quality Engineering to own the quality strategy, automation roadmap, release readiness model, and QA team for the Ziing.ai platform. This is a senior leadership role for someone who can move Ziing from manual‑heavy QA toward a modern, automation‑led Quality Engineering function. Manual testing will continue to matter, especially for exploratory testing, operational edge cases, usability, field validation, and release‑risk assessment. The core mandate, however, is to make quality repeatable, measurable, automated, and embedded into the software delivery lifecycle. You will lead QA engineers, SDETs, automation engineers, and manual testers while partnering deeply with engineering, product, operations,



customer success, support, data, security, and executive leadership. You will define how Ziing.ai validates quality across web applications, mobile driver workflows, APIs, routing and dispatch workflows, customer‑facing experiences, partner workflows, compliance controls, analytics, financial reconciliation, and AI‑enabled decision support. This is not a traditional QA management role. It is a platform quality leadership role. You will build the systems, standards, people, and operating rhythms that allow Ziing.ai to ship faster with higher confidence as the platform expands across customers, regions, delivery models, partners, and operational use cases. Quality Engineering Strategy and Roadmap

Own the overall Quality Engineering strategy for the Ziing.ai platform. Build and maintain the QA roadmap across automation, manual testing, test infrastructure, test data, CI/CD quality gates, release governance, observability, performance testing, and team capability. Define what “quality” means for Ziing.ai across reliability, usability, operational accuracy, compliance, financial accuracy, performance, mobile stability, API integrity, and release readiness. Move QA earlier into the product and engineering lifecycle by ensuring testability, observability, data requirements, acceptance criteria, and risk areas are defined before development is complete. Create a practical model for when to automate,



when to use exploratory/manual testing, when to use production monitoring, and when to block a release. Explore practical AI‑assisted QA workflows, including test case generation, test data synthesis, defect triage, log analysis, flaky test investigation, and change‑impact analysis. Partner with design and product to validate usability, accessibility, workflow clarity, and operational speed. Create web quality standards for UI behavior, error handling, loading states, permissions, auditability, and workflow completion. Release Governance and Quality Gates

Define release readiness criteria across automated test results, manual validation, defect severity, open‑risk reviews, test coverage, performance, observability, customer impact, rollback readiness, and operational readiness. Create go/no‑go decision frameworks for major releases, mobile releases, customer‑impacting changes, partner workflow updates, and platform changes. Ensure release risk is visible to engineering, product, operations, support, and executive stakeholders. Partner with engineering leadership to reduce failed releases, escaped defects, emergency fixes, and regression churn. Metrics, Dashboards, and Quality Outcomes

Define and own quality metrics that connect QA work to business and engineering outcomes. Build dashboards that provide clear visibility into product quality, release readiness, test coverage, mobile stability, web regression health, API quality, and operational risk. Use production defects, support tickets, customer feedback, observability data, and field issues to continuously improve the test strategy. Lead, coach, and develop a team of QA engineers, automation engineers, SDETs, m

📌 Director, Quality Engineering (Calgary)
🏢 Ziing Group
📍 Calgary