Ralph Lauren Quality Engineer

BoF Careers; Nutley (NJ); On-site; USD 120,000 - 170,000; Full time

Job summary

Ralph Lauren Corporation is seeking a hands-on Quality Engineer - Automation & AI in New Jersey. The role focuses on developing reliable UI, API, and end-to-end automation while modernizing frameworks and contributing to CI/CD pipelines.

You will create AI-assisted tools to improve testing efficiency and delivery feedback across teams, including QA, Product, Engineering, and DevOps. You will collaborate to improve test coverage, data handling, and framework compliance, using AI to accelerate

Qualifications

• Bachelor's degree in computer science, Engineering, IT, related field or equivalent experience.
• 5+ years of hands-on experience in Quality Engineering, SDET, test automation, or software development.
• Proficiency in Python, Java, or TypeScript with frameworks such as Playwright, Rest Assured, and Appium or similar automation tools, including reusable test components.
• Experience building CI/CD pipelines and integrating automated test suites using Jenkins, Bitbucket, GitHub, or similar tools.
• Hands‑on exposure to enterprise AI development tools and platforms such as Cursor, Microsoft Copilot, or comparable approved technologies.
• Strong debugging, root‑cause analysis, communication, and collaboration skills.

Responsibilities

• Develop and maintain automated tests for web, API, integration, and end-to-end business flows.
• Build and modernize maintainable automation frameworks using reusable components, libraries, and engineering standards.
• Optimize test execution, logging, reporting, troubleshooting, and maintainability across automation solutions. AI-Assisted Quality Engineering
• Build reusable AI-assisted utilities that solve practical Quality Engineering challenges.
• Use approved AI and LLM tools to accelerate test design, automation development, refactoring, and documentation
• Apply AI to generate test data, analyze failures and logs, support defect triage, and improve test coverage.
• Validate AI-generated outputs for accuracy, edge cases, maintainability, security, and framework compliance.
• Integrate smoke, regression, API, and integration tests into CI/CD workflows using Jenkins, Bitbucket Pipelines, GitHub Actions, Azure DevOps, or comparable tools.
• Implement automated quality gates and clear reporting to provide fast, actionable feedback to delivery teams.
• Partner with Engineering and DevOps to improve test environments, deployment validation, and pipeline stability.
• Identify repetitive testing and engineering activities and automate them through reusable tools for test data, environment setup, API validation, orchestration, and troubleshooting.
• Contribute to technical discussions, design reviews, and code reviews with a focus on quality, testability, and automation.
• Collaborate with globally distributed stakeholders and document standards, solutions, examples, and reusable automation patterns.

Skills

Python

Java

TypeScript

Playwright

CI/CD

AI tools

Education

Bachelor's degree in computer science or related field

Tools

GitHub Actions

Bitbucket Pipelines

Azure DevOps

Rest Assured

Appium

Job description

Company Description

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands. At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

Company Description

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands. At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

Position Overview

Who we are: Ralph Lauren Corporation is a global leader in the design, marketing, and distribution of premium lifestyle products across apparel, home, accessories, and fragrances. Ralph Lauren is recognized globally for timeless style, premium experiences, and a distinctive brand portfolio serving customers across international markets. Purpose & Scope: Ralph Lauren Consumer Technology is seeking a hands-on Quality Engineer - Automation & AI to develop reliable UI, API, integration, and end-to-end automation. The engineer will modernize reusable frameworks and utilities, contribute automated quality checks to CI/CD pipelines, and use approved AI-assisted tools to improve testing efficiency and delivery feedback. Working across Quality Engineering, Product, Engineering, and DevOps, this role will improve execution reliability, test coverage, reporting, and delivery feedback while resolving automation, data, environment, and integration issues. The engineer will also create practical AI-assisted accelerators for test design, code development, test data, failure analysis, and documentation, with all generated outputs reviewed for accuracy, maintainability, security, edge cases, and compliance.

Essential Duties & Responsibilities

• Develop and maintain reliable automated tests for web, API, integration, and end-to-end business flows.


• Build and modernize maintainable automation frameworks using reusable components, libraries, and engineering standards.


• Optimize test execution, logging, reporting, troubleshooting, and maintainability across automation solutions. AI-Assisted Quality Engineering


• Build reusable AI-assisted utilities that solve practical Quality Engineering challenges.


• Use approved AI and LLM tools to accelerate test design, automation development, refactoring, and documentation


• Apply AI to generate test data, analyze failures and logs, support defect triage, and improve test coverage.


• Validate AI-generated outputs for accuracy, edge cases, maintainability, security, and framework compliance. CI/CD and Continuous Quality


• Integrate smoke, regression, API, and integration tests into CI/CD workflows using Jenkins, Bitbucket Pipelines, GitHub Actions, Azure DevOps, or comparable tools.


• Implement automated quality gates and clear reporting to provide fast, actionable feedback to delivery teams.


• Partner with Engineering and DevOps to improve test environments, deployment validation, and pipeline stability. Engineering Productivity and Collaboration


• Identify repetitive testing and engineering activities and automate them through reusable tools for test data, environment setup, API validation, orchestration, and troubleshooting.


• Contribute to technical discussions, design reviews, and code reviews with a focus on quality, testability, and automation.


• Collaborate with globally distributed stakeholders and document standards, solutions, examples, and reusable automation patterns.

Required Qualifications

Experience, Skills & Knowledge

• Bachelor's degree in computer science, Engineering, IT, related field or equivalent experience


• 5+ years of hands-on experience in Quality Engineering, SDET, test automation, or software development.


• Proficiency in Python, Java, or Typescript with frameworks such as Playwright, Rest Assured, and Appium or similar automation tools, including reusable test components.


• Experience building CI/CD pipelines and integrating automated test suites using Jenkins, Bitbucket, GitHub, or similar tools.


• Hands‑on exposure to enterprise AI development tools and platforms such as Cursor, Microsoft Copilot, or comparable approved technologies.


• Strong debugging, root‑cause analysis, communication, and collaboration skills. Preferred Qualifications


• Demonstrated experience in applying LLMs, retrieval‑augmented generation (RAG), AI agents, and agentic workflows to enhance test generation, failure analysis, test optimization, self‑healing automation, and ongoing maintenance.


• Experience with prompt engineering, prompt regression testing, AI evaluation, and safety guardrails.


• Experience building reusable automation utilities, internal engineering tools, or accelerators, including modernization or migration of automation frameworks.


• Knowledge of microservices, cloud‑native applications, containers, distributed systems, SQL, data validation, and test‑data management.


• Full stack development experience is a plus. What You Bring


• Strong bias for action - proactively identify quality risks and translate innovative ideas into practical, scalable QE solutions.


• Challenge conventional approaches, experiment responsibly, and implement prototypes, reusable accelerators, and production‑ready improvements.


• Drive end‑to‑end ownership from requirements through implementation, adoption, and support while balancing speed, maintainability, security, and responsible AI validation.


• Share reusable patterns and lessons learned to strengthen engineering capability across the QE team.