Team Summary
Staples Print is the online print and marketing solutions division of Staples. Our print technology systems team goes beyond traditional IT. We are a team of passionate, collaborative, agile, and customer-obsessed problem solvers who believe great print experiences start with great software. We are driven by a commitment to making it easy for businesses and individuals to bring their ideas to life from business cards and banners to custom marketing materials and beyond.
We are intellectually curious, embrace emerging technologies, and constantly seek ways to modernize and scale our platform. We anticipate the evolving needs of our customers and business partners and deliver reliable, high-performance technology solutions that power millions of print orders. We move fast, think big, and take pride in building experiences that are seamless, personalized, and delightful for every customer.
Role Summary
As a Senior Quality Engineer Test Automation, you will own the design, implementation, and continuous improvement of automated testing frameworks for Staples Print's eCommerce platform. You will establish testing strategies that span functional, regression, performance, and API layers and increasingly, AI-powered feature validation ensuring high-quality releases across web and service tiers. You will integrate automated tests into CI/CD pipelines, drive shift-left quality practices, leverage AI-assisted testing tools to improve efficiency, and mentor junior QE engineers. This is a hands-on role that requires deep automation expertise, strong analytical skills, and a proactive, forward-looking quality mindset.
Duties & Responsibilities
-Design, build, and maintain end-to-end automated test frameworks for web UI, API, and service-layer testing.
-Develop and maintain automated test suites using Selenium WebDriver, Playwright, or equivalent tools for functional and regression coverage.
-Build and execute performance and load testing scenarios using StressStimulus, Apache JMeter, Gatling, or equivalent tools; analyze results and report findings to engineering teams.
-Create and maintain API test automation using RestAssured, Postman/Newman, or Karate Framework.
-Integrate automated test suites into CI/CD pipelines (Azure DevOps, GitHub Actions, or Jenkins) to enable continuous quality gates.
-Apply AI-assisted tools such as GitHub Copilot or AI-based test generators to accelerate test script creation, reduce maintenance burden, and explore how AI can improve testing efficiency.
-Contribute to testing AI-powered application features including verifying output correctness, flagging unexpected behaviors, and working with the team on how to handle variability in AI-generated responses.
-Stay current with AI testing tools and techniques, proactively experimenting with new approaches and sharing findings with the team to continuously improve quality practices.
-Contribute to developing acceptance criteria for AI-generated content considering factors like relevance, tone, and accuracy in collaboration with product and engineering teams.
-Define and own test strategies, test plans, and test coverage matrices aligned to product requirements.
-Collaborate with development engineers during feature development to influence testability, design, and acceptance criteria.
-Perform exploratory, functional, regression, and smoke testing across web and API layers as needed.
-Triage, reproduce, and clearly document defects; track resolution and validate fixes.
-Analyze test results, identify failure patterns, and drive root-cause analysis on recurring quality issues.
-Champion quality metrics test coverage, defect escape rate, automation ROI and report to engineering leadership.
-Mentor junior QE engineers on automation practices, tooling, and quality-first mindset.
-Evaluate and recommend new testing tools, frameworks, and methodologies to continuously improve quality practices.
Requirements
Years of Experience
Minimum of 3 years of experience in an eCommerce and automation engineering lead role.
Minimum of 2 years of experience working with high-traffic, large-scale distributed systems and cloud platforms.
Basic Qualifications
-Bachelor’s degree in computer science, Information Systems, Engineering, or a related field, or equivalent experience.
-4+ years of experience in software quality engineering with at least 3 years focused on test automation.
-Strong hands-on expertise with Selenium WebDriver for web UI automation (Java or C# preferred).
-Experience with at least one modern UI automation framework: Playwright, Cypress, or TestCafe.
-Experience with performance and load testing tools: StressStimulus, Apache JMeter, Gatling, or k6.
-Experience with API test automation: RestAssured, Postman/Newman, Karate Framework, or equivalent.
-Experience integrating automated tests into CI/CD pipelines (Azure DevOps, GitHub Actions, or Jenkins).
-Proficiency with at least one scripting/programming language: Java, C#, Python, or JavaScript/TypeScript.
-Strong understanding of the Software Testing Life Cycle (STLC), test design techniques, and defect management.
-Exposure to testing applications that include AI or ML-generated outputs, with an understanding that AI responses may vary and require different validation approaches than deterministic logic.
-Awareness of AI-assisted testing tools (e.g., GitHub Copilot for test generation, Testim, Mabl, or equivalent).
-Experience with test management tools (Azure Test Plans, Xray, TestRail, or JIRA).
-Familiarity with Page Object Model (POM) or similar design patterns for test framework architecture.
-Experience with Git and version control practices for test code.
-Excellent analytical, communication, and collaboration skills.
Preferred Qualifications
-Experience with BDD frameworks: Cucumber, SpecFlow, or Behave.
-Familiarity with contract testing tools (Pact or Spring Cloud Contract).
-Experience with accessibility testing tools (Axe, WAVE, or equivalent).
-Exposure to visual regression testing (Percy, or similar).
-Experience testing microservices, event-driven systems, or cloud-native applications on Azure.
-Any hands-on experience with AI-assisted testing tools such as GitHub Copilot for writing tests, even in personal or academic projects.
-Familiarity with how Generative AI features are evaluated including awareness of concepts like output scoring or semantic comparison and an interest in applying these in a QE context.
-Experience in retail or eCommerce quality engineering contexts.
-Exposure to chaos engineering or resiliency testing methodologies.
-Familiarity with observability tools (Application Insights, Splunk) for test failure diagnostics.