Principal, QA Engineer

Job Description
Job Purpose
The Principal QA Engineer will serve as a technical leader and architect within the QA organization, with a primary focus on designing and developing tools, frameworks and automated solutions to accelerate and streamline the QA team's testing efforts. This role goes beyond traditional testing - it's about enabling scalable, efficient and high-impact testing practices for trading tools that integrate real-time cross-asset data, global news and analytics in a unified platform.

The Principal QA Engineer is responsible for architecting test automation frameworks and tooling solutions to enable scalable, efficient and modern testing practices. This role will partner closely with development, product and QA teams to improve quality across the entire SDLC.

The ideal candidate is a seasoned SDET with a strong command of QA principles, tools, and automation. They will tackle complex QA challenges, influence strategic quality initiatives, and drive continuous improvement in test coverage, automation, and infrastructure. This role requires the ability to assess applications objectively, collaborate with stakeholders to understand requirements, and partner with developers to evaluate architectural changes, debug issues, and enhance overall quality.

Responsibilities

• Quality Engineering Architecture & Tooling: Lead the design and development of custom tools, test harnesses and automation frameworks to support functional, integration, performance and end-to-end testing. Build infrastructure that empowers QA engineers to test more effectively.
• AI-Driven QA Innovation: Lead the integration of AI technologies into QA workflows to enhance efficiency, scalability and predictive capabilities. This includes leveraging AI for intelligent test case generation, defect prediction, log analysis and self-healing automation. The role also promotes the adoption of AI-powered reporting and decision-support tools to elevate the strategic impact of quality assurance across the organization.
• Test Automation Strategy & Execution: Define and execute robust automation strategies that align with system architecture. Guide the team in identifying automation opportunities, improving coverage, and integrating tests into CI/CD pipelines.
• Test Infrastructure & Environment Management: Drive the setup, maintenance, and optimization of QA test environments and data to reflect production-like conditions. Ensure environments are scalable and reliable for automated and exploratory testing.
• SDET Leadership & Mentorship: Provide technical mentorship to QA and SDET engineers. Review test architecture and code for quality, efficiency and maintainability.
• Cross-Team Collaboration: Partner with developers, DevOps and product managers to review requirements and architecture for testability and design. Actively participate in planning sessions to influence design with quality in mind.
• Testing Strategy & Test Case Design: Lead the development of comprehensive test strategies that cover functional, performance, security, and edge-case scenarios.
• Documentation & Reporting: Produce technical documentation for tools and frameworks developed. Contribute to quality dashboards and provide transparency into test progress, coverage, and results.
• Continuous Improvement & QA Governance: Drive continuous improvements in process, tooling and reporting. Establish quality gates and metrics to monitor effectiveness and influence team-wide decisions.
• Quality Advocacy & Problem Solving: Maintain a strong quality mindset with a "break-it to make-it better" attitude, while also being a proactive problem solver who contributes to root cause analysis and continuous improvement.

Knowledge And Experience

• 10+ years of related work experience.
• Strong written and verbal communication skills.
• Strong analytical and problem-solving skills.
• Strong understanding machine learning principles and their application in software testing.
• Experience with mainstream defect tracking tools and test management tools.
• Implementing AI/ML solutions to optimize QA workflows and test coverage.
• Designing intelligent test case generation and predictive defect analysis systems.
• Applying NLP for requirement parsing, log analysis, and automated test creation.
• Building self-healing automation frameworks that adapt to UI/API changes.
• Integrating AI-powered monitoring and reporting into QA pipelines.
• Proficiency in Python, Java, or similar languages for scripting and model integration.
• Experience using test result reporting tools like Allure, Extent Reports or similar
• Proficient in CI/CD pipelines adhering to secure and compliant deployment practices using Coinbase and skilled in version control systems like Git collaborative development and code management.

List Of Preferred Degree(s), License(s), And/or Certification(s)
B.S. / M.S. in Computer Science, Electrical Engineering, Math or equivalent

Preferred Knowledge And Experience

• AI/ML certifications
• Experience in the financial industry, particularly with trading tools involving real-time cross-asset data and fixed income