VP: Lead Test Engineer(105026)

We are seeking an exceptional Vice President – Global QA Automation Lead to lead the next generation of Quality Engineering across a portfolio of strategic business applications. This role will own the global Quality Assurance strategy, establish AI-driven test automation practices, govern release quality, and provide independent QA sign-off for multiple mission-critical systems.

The successful candidate will combine deep expertise in Java, Selenium, enterprise automation frameworks, and modern quality engineering practices with practical experience leveraging Artificial Intelligence (AI) for testing, test generation, defect prediction, intelligent automation, and engineering productivity.

This individual will be a highly visible technology leader capable of engaging effectively with senior business stakeholders, technology executives, and global delivery teams while driving a transformation towards an automation-first and AI-first quality engineering culture.

Experience within Equity Derivatives, Structured Products, Front Office Trading Platforms, or Capital Markets is strongly preferred.

• Own and define the global Quality Engineering vision, strategy, governance, and operating model.
• Establish enterprise-wide quality standards, testing controls, automation frameworks, and release governance processes.
• Provide QA sign-off and release readiness assessments across multiple strategic platforms and programmes.
• Act as the final quality authority for production releases, ensuring risk-based decision making.
• Drive quality transformation initiatives across globally distributed teams.
• Establish quality KPIs and executive dashboards for quality visibility and governance.

• Define and execute the enterprise AI-powered Quality Engineering roadmap.
• Drive adoption of Generative AI and AI-assisted testing capabilities across the SDLC.
• Develop strategies leveraging AI for:
  • Automated test case generation
  • Test script generation
  • Intelligent regression selection
  • Defect prediction and root cause analysis
  • Risk-based testing
  • Synthetic test data generation
  • Release quality intelligence
• Evaluate and implement emerging AI testing platforms and engineering tools.
• Build organizational capability around AI-enabled quality engineering practices.
• Partner with Engineering teams to establish AI-accelerated software delivery patterns.

• Define global test automation architecture and engineering standards.
• Design and govern scalable automation frameworks built using Java and Selenium.
• Establish reusable automation assets, libraries, frameworks, and testing accelerators.
• Drive automation coverage across:
  • UI Testing
  • API Testing
  • Integration Testing
  • End-to-End Testing
  • Data Validation Testing
  • Performance Testing
• Promote shift-left testing, continuous testing, and quality gates within CI/CD pipelines.

• Define comprehensive testing strategies for large-scale transformation initiatives.
• Ensure complete business requirement traceability and test coverage.
• Drive adoption of risk-based testing approaches.
• Establish test governance frameworks covering quality metrics, release controls, and production risk management.
• Lead quality reviews and executive-level quality reporting.

• Build trusted relationships with business leaders, Front Office stakeholders, Product Owners, and Technology Leadership.
• Translate complex business requirements into comprehensive quality engineering solutions.
• Clearly communicate quality risks, test progress, and release readiness to senior stakeholders.
• Partner with global delivery teams to ensure consistent quality execution across regions.

• Lead globally distributed QA and Automation teams.
• Build a high-performance engineering culture focused on innovation and continuous improvement.
• Mentor senior QA engineers, automation architects, and quality managers.
• Drive adoption of modern engineering and AI testing practices.
• Develop organizational automation maturity and quality engineering capabilities.

• 15+ years of experience in Software Testing, Quality Engineering, and Test Automation.
• 8+ years leading enterprise-wide QA Automation initiatives.
• Extensive experience providing release sign-off and quality governance.
• Proven success leading globally distributed quality engineering teams.
• Demonstrated experience driving organization-wide quality transformations.

Strong hands-on experience in:

• Core Java
• Selenium WebDriver
• TestNG / JUnit
• Cucumber / BDD Frameworks
• REST API Testing
• Microservices Testing
• SQL & Database Testing
• GitLab
• CI/CD Automation
• Automation Framework Design
• Design Patterns & Test Architecture

Must have direct experience designing and owning large-scale automation frameworks, not merely executing automated tests.

Candidates must demonstrate practical experience using AI within Software Testing and Quality Engineering.

Examples include:

• Using Generative AI tools for test design and automation generation.
• AI-assisted creation of automated test scripts.
• AI-driven defect triage and root cause analysis.
• Intelligent test selection and regression optimization.
• AI-powered quality analytics and release intelligence.
• LLM-based testing approaches.
• Agentic AI solutions supporting SDLC and Quality Engineering activities.

The ideal candidate should be able to articulate a clear vision for how AI will transform testing over the next 3–5 years and have evidence of implementing such solutions in production environments.

Strong knowledge of:

• Capital Markets
• Equity Derivatives
• Equity Options
• Structured Products
• Equity Structured Notes
• Front Office Technology
• Trading Platforms
• Order Management Systems (OMS)
• Pricing Systems
• Trade Lifecycle Management