Digital Technology Manager - Test Architecture

About the job :

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.

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.

Ralph Lauren Consumer Technology is seeking a Senior Test Architect - Quality Engineering to define and scale a modern quality architecture for AI-enabled commerce experiences, digital platforms, and enterprise quality workflows.

Responsibilities :

- Define, drive and build the end-to-end test architecture and governance model for AI-enabled systems, digital commerce platforms, and composable technology programs.

- Evaluate, pilot, and introduce AI-powered testing tools, autonomous testing platforms, observability solutions, and engineering productivity tools.

- Create AI-aware validation strategies for Ask Ralph, Outfitting, and similar features, covering prompt behavior, answer relevance, groundedness, hallucination risks, bias, drift, data quality, guardrails, latency, and cost.

- Define non-functional testing strategy across performance, scalability, reliability, resilience, accessibility, security validation support, observability, SLO/SLI alignment, and production-readiness gates.

- Mentor QE engineers, SDETs, and align with POD teams on quality architecture, AI-assisted quality practices, automation design, test data strategy, and modern engineering discipline.

- Partner with engineering teams to embed quality gates into CI/CD pipelines, including smoke, regression, deployment verification, synthetic monitoring, and release-readiness checks.

- Prepare and present executive-level quality insights, risks, adoption progress, and recommendations to global stakeholders.

- Design scalable automation frameworks for UI, API, integration, contract, mobile apps, visual, accessibility, performance, resilience, and AI system testing using modern frameworks such as DeepEval, Ragas, Playwright, Selenium, Appium, RestAssured, PyTest, and equivalent tools.

- Create requirement review practices using AI to identify ambiguity, missing acceptance criteria, edge cases, testability gaps, dependency risks, compliance concerns, and impacted regression areas.

- Lead automated script generation using AI by defining standards, prompt libraries, reusable patterns, review gates, and secure practices.

- Architect auto-healing automation capabilities that can detect locator failures, diagnose root causes, recommend or apply safe locator fixes, and feed learning back into the framework.

- Implement AI-driven defect categorization for automation failures, including flaky test detection, failure clustering, root-cause suggestions, and feedback loops.

- Build quality insights and observability dashboards covering automation health, coverage, code-review insights, release gates, failure trends, environment readiness, defect leakage, and end-to-end product quality signals.

- Establish AI-powered visual validation for web and mobile experiences, including layout drift, brand consistency, localization differences, responsive behavior, and high-risk customer journey checks.

- Drive AI PR review capabilities for automated pull request feedback related to test coverage, locator strategy, automation design, code quality, risk areas, and adherence to framework standards.

- Enable AI-assisted test case generation from requirements, user stories, acceptance criteria, design documents, production analytics, and defect history.

Required Experience :

- Bachelor's or master's degree in computer science, Engineering, Information Technology, or equivalent practical experience.

- 12+ years of progressive experience in quality engineering, test architecture, automation engineering, SDET leadership, or related technical architecture roles.

- Demonstrated 7+ years of experience defining quality architecture, automation strategy, CI/CD quality gates, and test governance.

- 2+ years of focused experience in automating testing for AI-enabled applications using metrics such as answer relevance, groundedness, hallucination detection, toxicity/safety checks, latency, cost, and regression consistency.

- Strong understanding of AI/ML and GenAI concepts including LLMs, RAG, embeddings, vector databases, inference behavior, prompt engineering, agentic workflows, and AI evaluation methods.

- Hands-on expertise in automation frameworks and programming languages such as Playwright, Selenium, JavaScript/TypeScript, Python, Java, PyTest, RestAssured, Postman, and API automation frameworks, DeepEval, or equivalent tools.

- Experience integrating automation suites into CI/CD platforms such as Jenkins, Bitbucket Pipelines, GitHub Actions, Azure DevOps, or equivalent tools.

- Strong understanding of observability and reporting tools such as Grafana, Splunk, Datadog, ReportPortal, ELK, or similar platforms.

- Experience with cloud-native, microservices, API-driven, and composable architecture environments.

- Fluency in agile delivery, test strategy creation, defect governance, release readiness, and risk-based testing.

- Strong communication and stakeholder management skills.

Skills

Software Quality Assurance, SDET, Automation Testing, Test Architect, GUI Testing, API Testing, Selenium, Appium, RestAssured, PyTest, Python