GHN

Overview of job

As the Principal Quality Engineer at GHN, you will join a high-impact, technology-driven team responsible for the next-generation GHN Platform — the integrated system powering shipment operations, logistics routing, delivery execution, enterprise services, and customer-facing experiences across Vietnam. You will:

• Define and lead the overall quality strategy, standards, and practices for the GHN Platform — ensuring our logistics, delivery, tracking, and operational systems meet the highest standards of reliability, security, performance, scalability, and compliance.
• Act as a strategic partner across product, engineering, operations, data, and business teams to drive test planning, automation and continuous improvement of end-to-end business flows — from order intake, routing, delivery execution, real-time status updates, exception handling, through to returns and reporting.
• Architect and oversee the implementation of a robust automation and monitoring framework: integration tests, API tests, end-to-end workflow tests, observability tooling, scenario/failure-mode coverage for all major platform services and integrations (internal systems, partner APIs, mobile/web apps).
• Establish and embed performance, stress, scalability and resiliency testing practices and governance to ensure the GHN Platform can handle high transaction volumes, rapid growth, peak-period bursts and evolving business demands.
• Champion advanced quality engineering practices: shift-left testing, “testability by design”, CI/CD-pipeline integration, production observability, incident management feedback loops, and quality data-driven decision-making.
• Define, monitor and report on platform quality KPIs (e.g., service-level metrics, defect leakage rate, automation coverage, system-uptime, mean-time-to-detect/fix, cycle time), surface risk trends, drive root-cause analysis and preventative actions, and elevate the QE craft across the organization.
• Serve as a mentor and technical leader: guide and develop other quality engineers and QA-team members, foster a culture of quality ownership across product & engineering teams, evangelize best practices and practise hands-on problem solving and tooling improvements.

• 13th-month salary, performance bonuses, and KPI bonuses
• Health insurance, Social insurance, and Unemployment insurance
• Medical insurance
• Annual health checkup
• Annual salary reviews
• Annual team building/company trip
• Ongoing internal and external training opportunities.

• 8+ years of end-to-end Quality Engineering experience, with at least 3–5 years in senior or principal-level roles leading quality strategy, automation architecture, and platform-scale reliability initiatives.
• Proven experience designing quality frameworks for distributed systems, microservices, and high-throughput platforms (e.g., logistics, e-commerce, fintech, SaaS).
• Deep hands-on expertise in test automation frameworks, API testing, service-level validation, end-to-end workflow automation, and integration into CI/CD pipelines (GitLab, GitHub Actions, Jenkins, ArgoCD).
• Strong background in performance, scalability, stress, and resiliency testing, including chaos testing and failure-mode analysis for mission-critical systems.
• Excellent analytical and problem-solving skills — capable of interpreting logs, metrics, traces, and system behaviors to pinpoint root-causes across complex architectures.
• Demonstrated ownership mindset, capable of driving cross-team initiatives and elevating engineering quality at organizational scale.
• Strong communication and leadership skills, able to influence product, engineering, data, and operations teams.
• Deep understanding of observability tooling (Grafana, Prometheus, Datadog, ELK/OpenSearch, Tempo, Jaeger) and proficiency in triaging large-scale incidents.
• Familiarity with Agile product development, quality governance, and engineering processes using tools like Jira, Notion, ClickUp or similar.
• Experience applying AI/ML techniques for improving QE productivity (e.g., test case generation, anomaly detection, log intelligence, defect prediction).
• Ability to evaluate or integrate AI-powered testing tools (e.g., intelligent test selection, semantic comparison, automated root-cause analysis).
• Understanding of ML model quality metrics (accuracy, drift, precision/recall) and experience validating AI-driven systems is a strong plus.
• Hands-on experience building or integrating AI agents or automation pipelines to accelerate QE workflows is highly desirable.
• Experience in logistics, supply chain, fintech, payments, reconciliation, or other high-volume transactional domains is a plus — but not required.
• Passion for user-centric, data-driven, continuously improving products; strong alignment with GHN’s product & engineering culture.