This is a remote position.
Principal Quality Automation Architect
Reporting to Manager Quality Engineering & AI Validation designs and scales Accordions automated quality framework across products services and AI-enabled workflows. Owns the architecture behind automated validation test harnesses evaluation pipelines test data strategy and cross-pod tooling standards.
Key Responsibilities
Automation Architecture
Design and implement the core automation framework for functional API integration regression and workflow testing.
Define standards for reusable test assets environment usage data setup and evidence capture.
Create scalable approaches to testing complex multi-system workflows.
AI Evaluation Infrastructure
Build and maintain regression harnesses for AI-enabled features including prompt and workflow comparisons scored evaluation runs and benchmark execution.
Partner with AI quality analysts to support rubric-based testing and measurable release criteria.
Test Data & Environment Strategy
Define approaches for test data synthetic data masked data and scenario generation.
Improve reliability and repeatability of validation environments.
Engineering Partnership
Work closely with software engineers to improve testability observability CI/CD integration and defect prevention.
Help pods move quality checks earlier in the development lifecycle.
Requirements
Required Qualifications
7 years of experience in QA automation SDET or quality engineering roles.
Strong experience with test automation frameworks API testing CI/CD and integration validation.
Strong scripting or coding skills.
Experience working with data-intensive or workflow-heavy applications.
Exposure to AI or LLM validation tooling or strong interest in building in that space.
Ability to design frameworks not just individual tests.
Bachelors degree preferred.
Key Traits for Success
Systems-minded and deeply technical.
Focused on scale repeatability and leverage.
Comfortable setting standards others adopt.
Practical about balancing sophistication with delivery pace.
Benefits
Base salary plus performance-based bonus.
Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate including but not limited to skill set years and depth of experience education certifications cost of labor and internal equity.
Required Skills:
10 years of experience in Quality Engineering Test Automation or QA Architecture Proven experience designing and implementing enterprise-level automation frameworks Strong hands-on experience with automation tools (e.g. Selenium Cypress Playwright or similar) Experience with API testing frameworks and microservices architectures Deep understanding of cloud platforms (AWS and/or Azure) Strong experience validating data pipelines ETL/ELT processes and data platforms Experience with CI/CD tools (e.g. Jenkins GitHub Actions Azure DevOps) and DevOps practices Strong programming/scripting experience (e.g. Python Java or JavaScript) Expertise in SQL and data validation techniques
This is a remote position. Principal Quality Automation Architect Reporting to Manager Quality Engineering & AI Validation designs and scales Accordions automated quality framework across products services and AI-enabled workflows. Owns the architecture behind automated validation test harnes...
This is a remote position.
Principal Quality Automation Architect
Reporting to Manager Quality Engineering & AI Validation designs and scales Accordions automated quality framework across products services and AI-enabled workflows. Owns the architecture behind automated validation test harnesses evaluation pipelines test data strategy and cross-pod tooling standards.
Key Responsibilities
Automation Architecture
Design and implement the core automation framework for functional API integration regression and workflow testing.
Define standards for reusable test assets environment usage data setup and evidence capture.
Create scalable approaches to testing complex multi-system workflows.
AI Evaluation Infrastructure
Build and maintain regression harnesses for AI-enabled features including prompt and workflow comparisons scored evaluation runs and benchmark execution.
Partner with AI quality analysts to support rubric-based testing and measurable release criteria.
Test Data & Environment Strategy
Define approaches for test data synthetic data masked data and scenario generation.
Improve reliability and repeatability of validation environments.
Engineering Partnership
Work closely with software engineers to improve testability observability CI/CD integration and defect prevention.
Help pods move quality checks earlier in the development lifecycle.
Requirements
Required Qualifications
7 years of experience in QA automation SDET or quality engineering roles.
Strong experience with test automation frameworks API testing CI/CD and integration validation.
Strong scripting or coding skills.
Experience working with data-intensive or workflow-heavy applications.
Exposure to AI or LLM validation tooling or strong interest in building in that space.
Ability to design frameworks not just individual tests.
Bachelors degree preferred.
Key Traits for Success
Systems-minded and deeply technical.
Focused on scale repeatability and leverage.
Comfortable setting standards others adopt.
Practical about balancing sophistication with delivery pace.
Benefits
Base salary plus performance-based bonus.
Actual compensation packages are determined by evaluating a wide array of factors unique to each candidate including but not limited to skill set years and depth of experience education certifications cost of labor and internal equity.
Required Skills:
10 years of experience in Quality Engineering Test Automation or QA Architecture Proven experience designing and implementing enterprise-level automation frameworks Strong hands-on experience with automation tools (e.g. Selenium Cypress Playwright or similar) Experience with API testing frameworks and microservices architectures Deep understanding of cloud platforms (AWS and/or Azure) Strong experience validating data pipelines ETL/ELT processes and data platforms Experience with CI/CD tools (e.g. Jenkins GitHub Actions Azure DevOps) and DevOps practices Strong programming/scripting experience (e.g. Python Java or JavaScript) Expertise in SQL and data validation techniques