Quality Assurance Engineering Lead

Responsibilities

• Define and drive the quality assurance strategy and testing roadmap for large-scale product areas, aligning cross-functional teams around shared quality objectives
• Architect and implement scalable test automation frameworks covering functional, regression, integration, and end-to-end testing across web and mobile platforms
• Identify systemic quality gaps through root cause analysis and implement corrective interventions that improve overall product reliability and test coverage
• Partner with engineering, product management, and data science teams to embed quality practices early in the development lifecycle, including requirements review and risk-based test planning
• Establish and monitor quality metrics, test coverage signals, and release health indicators to inform go/no-go decisions and communicate quality posture to leadership
• Lead the evaluation and adoption of AI-integrated testing workflows, including using AI tools to accelerate test generation, defect triage, and coverage analysis
• Coach and guide other engineers on test design principles, automation best practices, and quality-first development approaches
• Proactively identify high-impact quality risks across multiple product teams and drive mitigation strategies that reduce customer-facing defects
• Contribute to organizational quality standards and processes, influencing how quality engineering is practiced across teams and product areas
• Manage staged rollout validation using feature flagging and A/B testing frameworks to assess product quality in production environments

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• 8+ years of experience in quality assurance test engineering, including test strategy definition, test automation architecture, and release quality validation for consumer-facing or platform products
• 8+ years of experience designing and implementing scalable test automation frameworks across functional, integration, regression, and end-to-end testing domains
• Experience leading cross-functional quality initiatives, influencing engineering and product teams on quality standards, risk assessment, and testing methodologies
• Experience analyzing quality metrics, defect trends, and test coverage data to drive measurable improvements in product reliability and release confidence
• Experience with feature flagging systems, staged rollout validation, and production quality monitoring as part of a continuous delivery pipeline

Preferred Qualifications

• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
• Experience defining quality assurance strategy for mobile platforms (iOS and Android) at scale, including device fragmentation and platform-specific testing challenges
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated track record of building quality engineering programs or centers of excellence that raised quality standards across multiple product teams
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience applying AI or machine learning tools to accelerate test generation, defect classification, or coverage gap analysis in a software quality context
• Experience with performance testing, load testing, or chaos engineering methodologies to validate product reliability under real-world conditions

Compensation

• $163,000/year - $224,000/year; Country: US; Bonus eligible; Equity eligible

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