Quality Assurance Engineering Lead

Meta•Burlingame, CA

9d•$163,000 - $224,000

About The Position

Meta is seeking a Quality Assurance Test Engineer to drive product quality strategy across large-scale consumer and platform products. In this role, you will define and lead quality assurance frameworks, establish testing methodologies, and partner with engineering, product, and data science teams to ensure that Meta's products meet the highest standards of reliability, performance, and user experience. You will apply deep expertise in test architecture, automation, and quality systems to influence product roadmaps and shape how quality is built into the development lifecycle at scale.

Requirements

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

Nice To Haves

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

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