Director, Production Quality & Stability

2C2P Bangkok Metropolis, Thailand
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We are looking for a visionary and hands-on Director of Quality Engineering to lead our QA organization. As our international payment business scales, you will be the ultimate guardian of online stability and delivery efficiency.

Your core mission is to expedite the evolution of our current testing strategies, with a focus on fostering a high-availability, automation-first, AI-driven engineering practice. You will oversee the quality of complex payment information and fund flows, ensuring that our systems remain "financial-grade" stable while supporting rapid business growth.

Key Responsibilities

  1. Strategic Quality Governance & Stability • Total Quality Accountability: Take ownership of production stability and end-to-end quality for our global payment platform. • Stability Defense: Define fault scenarios based on deep product/business chain analysis. Implement proactive monitoring, circuit breaking, and stability prevention measures. • Environment Management: Establish and optimize rigorous regression and promotion gates across Dev, QA, UAT, and Production environments.

  2. Team Leadership & Global Collaboration • Global Team Management: Lead and mentor diverse, multi-national QA teams across international R&D centers, fostering a unified culture of excellence, accountability, and continuous learning. • Cross-Border Synergy: Drive alignment of quality standards and operational processes across all global R&D centers.

  3. Engineering Excellence & Automation • Modernization: Overhaul the current manual testing process by building a robust automation framework (Shift-left & Shift-right). • Full-Stack Testing: Drive the strategy for Regression, Performance (stress testing), Security (vulnerability scanning), Compatibility, and Data Consistency (SQL Server/MySQL/DynamoDB etc.). • Efficiency Metrics: Define and track KPIs focused on business delivery velocity and production defect leakage.

  4. AI & Innovation • AI-Driven QA: Pioneer the use of AI/LLMs and innovative tools to automate test case generation, anomaly detection, and intelligent traffic playback to solve efficiency bottlenecks.

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