Director, Quality Engineering

LiveRamp, Inc.•San Francisco, CA

32d•$204,500 - $295,000

About The Position

LiveRamp is seeking a Director, Quality Engineering to own end-to-end Product Quality strategy and execution across Infrastructure, Platform, Data, Application, APIs, Agents, and MCP-based systems. The role leads and grows a Quality Engineering organization of 40+ engineers and managers, drives AI-led transformation of quality processes and tooling, and establishes standard QE practices, frameworks, and quality gates across product lines. The Director owns the Observability platform strategy, quality-related Incident Management, and Product Quality governance, audit, and reporting processes. The role partners with Engineering, Product, Infrastructure, and Security leadership, and reports quality metrics, release risk, and readiness to senior leadership at VP Engineering level and above. Success is measured by reducing production incidents caused by quality gaps, increasing automated test coverage across Platform, Data, Infrastructure, Application, and Agent surfaces, making release cycles faster and more predictable, and demonstrating progress on the QE organization’s AI-transformation roadmap over the first 6, 12, and 18 months. The team works across every layer of LiveRamp’s platform, developing observability and automation systems and applying AI to modernize quality engineering.

Requirements

Bachelor’s degree in Computer Science, Information Technology, or a related field.
12–15+ years of experience in software quality or 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 such as Jenkins, Spinnaker, and 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 and partnering with QE embedded in scrum teams.

Nice To Haves

Master’s degree in Engineering or a Master of Science in Quality Assurance.
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 and analytics tools such as Tableau.
Experience working with or overseeing testing for AI agents and MCP-based systems.

Responsibilities

Own end-to-end Product Quality strategy and execution across Infrastructure, Platform, Data, Application, APIs, Agents, and MCP-based systems.
Lead and grow a Quality Engineering organization of 40+ engineers and managers, including hiring, coaching, career-path development, and performance management.
Drive AI-led transformation of quality engineering processes and tooling.
Define and enforce standard QE practices, frameworks, and quality gates across product lines.
Own the Observability platform strategy across test frameworks, coverage, monitoring, and alerting.
Own Incident Management processes for quality-related production issues, including root cause analysis and prevention.
Own governance and audit processes for Product Quality compliance and reporting.
Partner with Engineering, Product, Infrastructure, and Security leadership to align quality strategy with business goals.
Report quality metrics, release risk, and readiness to senior leadership, including VP Engineering and above.
Improve production quality, automated test coverage, release predictability, and progress on the QE organization’s AI-transformation roadmap.