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Starr Insurance

Global insurance and risk management provider

Director Quality Engineering - Automation & Quality Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-time$150k - $180kIn-person

About the Job

Requirements

  • A bachelor's degree in computer science, engineering, information systems, or a related field is required; a master's degree is preferred.
  • At least 12 years of experience in software quality engineering or quality assurance, including at least 5 years in management roles leading distributed teams.
  • Hands-on quality engineering experience in the Property & Casualty Insurance industry is required.
  • Expertise in building, scaling, and overseeing quality engineering operations, including automation frameworks, software development lifecycle integration, and test management.
  • Hands-on experience with automation technologies such as Selenium, Playwright, Cypress, Tosca, Appium, Postman, Rest Assured, Karate, JMeter, and performance engineering tools.
  • Experience integrating automated testing into continuous integration and continuous delivery pipelines using Azure DevOps, GitHub Actions, Jenkins, GitLab, or similar platforms.
  • A proven track record of driving automation adoption and measurable improvements in quality key performance indicators.
  • People leadership, team building, and stakeholder engagement skills.
  • Deep understanding of industry standards for security, compliance, and data privacy as they relate to quality engineering.
  • Experience managing teams in a global delivery model.
  • Knowledge of data quality assurance, cloud migration, and digital transformation initiatives.

Responsibilities

  • Lead, mentor, and develop a global Quality Engineering organization, including Quality Engineering Managers, Test Leads, Test Engineers, and Automation Specialists; provide direct oversight, set clear goals, and support professional development.
  • Define and execute enterprise-wide Quality Engineering and test automation strategies aligned with digital transformation and cloud modernization initiatives.
  • Establish automation as the default testing approach across functional, integration, API, data, performance, and regression testing.
  • Drive organizational adoption of modern quality engineering practices, including shift-left testing, shift-right validation, continuous testing, and quality observability.
  • Build a high-performance engineering culture focused on innovation, automation, accountability, and measurable quality outcomes.
  • Own the architecture, design, implementation, and continuous improvement of enterprise test automation frameworks and reusable quality platforms.
  • Drive automation across web, API, data, microservices, event-driven, and cloud-native applications.
  • Establish intelligent test automation capabilities using AI-assisted test generation, self-healing automation frameworks, predictive quality analytics, and risk-based testing approaches.
  • Develop scalable quality engineering platforms that enable teams to rapidly create, execute, and maintain automated tests with minimal manual intervention.
  • Standardize automation frameworks, coding standards, test design patterns, and engineering best practices across technology domains.
  • Partner with Engineering and DevOps leaders to implement automated quality gates within continuous integration and continuous delivery pipelines and deployment workflows.
  • Define and monitor Quality Engineering metrics, including automation coverage, automated execution rates, defect escape rates, release quality scores, mean time to detect and resolve defects, test execution efficiency, quality gate compliance, and production incident reduction.
  • Use data-driven insights and predictive analytics to identify quality risks, bottlenecks, and opportunities for optimization.
  • Develop executive-level quality dashboards that provide transparency into application health, release readiness, and automation maturity.
  • Drive measurable improvements in software quality, release predictability, and engineering productivity.
  • Champion adoption of emerging quality engineering technologies, including generative AI, machine learning-based test generation, autonomous testing, and intelligent quality platforms.
  • Lead enterprise initiatives to reduce manual testing effort through automation, reusable assets, and engineering enablement practices.
  • Continuously evaluate and modernize quality engineering tools, frameworks, and processes to improve scalability and effectiveness.
  • Establish communities of practice, training programs, and engineering standards that promote innovation and knowledge sharing across teams.
  • Drive root cause analysis initiatives and systemic quality improvements to eliminate recurring production defects.

About the Company

Starr Insurance

Global insurance and risk management provider

Starr Insurance provides commercial property and casualty insurance, plus travel and accident coverage, and also offers investment services for businesses across many industries. Its products are delivered through an underwriting process that assesses risk, then issues tailored policies to transfer that risk and cover losses, with support for claims and risk management. The company operates in 128 countries across six continents, giving it a global network and local market knowledge that help it cover almost any business location. Unlike others, Starr combines a long history (founded in 1919) with a wide international footprint and deep relationships in many markets, enabling it to serve clients wherever they do business. Its goal is to help customers succeed anywhere by providing broad insurance protection and financial solutions through its worldwide platform.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
New York City, New York
Founded
1919

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