Director, Quality Engineering at LiveRamp in San Francisco, CA
- Company: LiveRamp
- Location: San Francisco, CA
- Salary: $205K – $295K
- Job type: full time
- Workplace: onsite
- Posted: 2026-10-09
Job description
LiveRamp is shaping the future of responsible data collaboration between the world’s leading brands, retailers, financial services providers, and healthcare innovators. As consumers embrace new AI-driven experiences, the LiveRamp data collaboration network exponentially expands the breadth and accuracy of the data on which marketing AI capabilities operate, powering deeper customer insight and measurable performance on a global scale. LiveRamp is headquartered in San Francisco, California, with offices worldwide. Learn more at LiveRamp.com . Director, Quality Engineering You will: Own end-to-end Product Quality strategy and execution across Infrastructure, Platform, Data, Application, APIs, Agents, and MCP-based systems Lead and grow a QE organization of 40+ engineers and managers — hiring, coaching, building career paths, and managing performance Drive AI-led transformation of quality engineering processes and tooling across the org Define and enforce standard QE practices, frameworks, and quality gates across all product lines Own the Observability platform strategy across all layers — test frameworks, coverage, and monitoring/alerting Own Incident Management processes for quality-related production issues, driving root cause analysis and prevention Own Governance and audit processes for Product Quality compliance and reporting Partner cross-functionally with Engineering, Product, Infra, and Security leadership to align quality strategy with business goals Report on quality metrics, release risk, and readiness to senior leadership (VP, Engineering and above) Measures of success: reduction in production incidents tied to quality gaps, increased automated test coverage across Platform/Data/Infra/Application/Agent surfaces, faster and more predictable release cycles, and measurable progress on the QE org's AI-transformation roadmap over the first 6, 12, and 18 months Your team will: Solve the hardest quality problems at LiveRamp's scale — ensuring the reliability of a data collaboration platform trusted by hundreds of global brands. The team owns quality across every layer of the stack (platform, data, infrastructure, application, and emerging AI agent/MCP surfaces), builds the observability and automation systems that catch issues before customers do, and is at the forefront of applying AI to modernize how quality engineering is done. This is a high-visibility organization of 40+ engineers and managers working directly with Engineering, Product, Infra, and Security leadership to keep LiveRamp's products safe, reliable, and fast to ship. About you: Bachelor's degree in Computer Science, Information Technology, or a related field is required; a Master's degree in Engineering or a Master of Science in Quality Assurance is preferred 12-15+ years of experience in software quality/test engineering 5-8+ years of experience in QE leadership or people management, including building and scaling QE organizations of 40+ engineers Deep expertise in test strategy across Functional, Integration, End-to-End, Performance/Load, and Robustness testing Experience owning release quality for large-scale distributed and data systems, including cloud infrastructure such as GCP, Kubernetes, and AWS Experience with CI/CD platforms (Jenkins, Spinnaker, CircleCI) and modern test infrastructure at scale Experience setting up and owning Observability tooling across frameworks, monitoring, and alerting Experience leading Incident Management and driving Governance, audit, and compliance practices Strong executive communication and stakeholder management skills Experience operating in agile environments, partnering with QE embedded in scrum teams Preferred Skills: Experience integrating AI and automation into quality engineering processes and tooling Experience with backend data processing or data pipeline systems Familiarity with log analysis tools such as LogDNA, Datadog, or Kibana Familiarity with reporting/analytics tools such as Tableau Experience workin
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