Performance Engineer Analyst

Performance Engineer (Analyst) - 66692 - Ralph Lauren

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Performance Engineer (Analyst)

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Ref #

W177986

State/Region

New Jersey

Department

Information Technology

Location

United States

City

Nutley

Pay Range: The pay range for this job is $71500 - $142150 annually; actual pay is dependent on experience and geographic location.

Benefits: Base pay is only one part of our employee value proposition, which includes a robust benefits package, above-market time off, hybrid working arrangements, incentive compensation, where applicable, and varied learning opportunities.

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

Ralph Lauren is seeking a Performance Engineer (Analyst) to support the optimization, monitoring, and continuous improvement of our global digital commerce platform. This role will focus on ensuring fast, reliable, and measurable customer experiences across our composable architecture built on Next.js, HarperDB, and Akamai.

The Performance Engineer (Analyst) will work closely with Engineering, Architecture, QA, Product, and Platform teams to identify performance opportunities, implement monitoring solutions, automate testing processes, and provide actionable insights using observability platforms including Datadog, Catchpoint, and Akamai mPulse.

As Ralph Lauren continues to expand its digital and AI-driven customer experiences, the Performance Engineer (Analyst) will also support the performance, observability, and delivery of AI-enabled services and traffic patterns. This includes monitoring AI and LLM-driven traffic, evaluating the impact of generative AI integrations on customer experience, and ensuring that both human and AI consumers of Ralph Lauren's digital platforms receive reliable, scalable, and optimized experiences.

This role is ideal for an analytical and technically skilled professional who is passionate about web performance, observability, Core Web Vitals, and modern digital experiences. The successful candidate will help establish performance best practices, support release validation activities, and contribute to the overall performance governance program across Ralph Lauren's global digital ecosystem.

ESSENTIAL DUTIES & RESPONSIBILITIES

• Monitor, analyze, and improve application performance across browser, CDN, edge, API, and origin layers.
• Support performance optimization initiatives for Next.js applications, APIs, and composable commerce experiences.
• Configure, maintain, and enhance monitoring solutions utilizing Datadog, Catchpoint, and Akamai mPulse.
• Create and maintain dashboards, alerts, reports, and automated performance monitoring workflows.
• Analyze Core Web Vitals, user experience metrics, and synthetic monitoring data to identify performance opportunities and risks.
• Partner with development teams to improve rendering performance, caching effectiveness, and overall application responsiveness.
• Assist with CDN and edge optimization efforts, including cache strategy validation and performance analysis.
• Support performance testing activities across multiple regions, devices, browsers, and network conditions.
• Develop and maintain automated performance validation processes within CI/CD pipelines.
• Participate in release readiness reviews, performance testing, and post-deployment validation activities.
• Investigate performance incidents, conduct root cause analysis, and provide recommendations for remediation.
• Generate weekly and monthly performance reports that correlate synthetic, real user monitoring, and observability data.
• Collaborate with Engineering, Architecture, QA, and Product teams to establish and maintain performance standards and governance processes.
• Continuously evaluate new tools, technologies, and best practices related to performance engineering and digital experience monitoring.
• Monitor and analyze AI and LLM-generated traffic patterns to ensure optimal platform performance, scalability, and resource utilization.
• Support performance strategies for AI-enabled customer experiences, search capabilities, recommendation engines, and future generative AI integrations.
• Partner with engineering and architecture teams to establish observability and monitoring standards for AI-powered applications and services.
• Leverage AI-assisted observability capabilities within Datadog and other monitoring platforms to accelerate anomaly detection, root cause analysis, and performance troubleshooting.
• Analyze the impact of AI crawlers, bots, and automated consumers on application performance, caching effectiveness, and infrastructure utilization.
• Support initiatives that optimize traffic segmentation, delivery, and performance for both human users and AI consumers across the digital ecosystem.

EXPERIENCE, SKILLS & KNOWLEDGE

Required Qualifications

• 3-5+ years of experience in Performance Engineering, Performance Analysis, Site Reliability Engineering, Application Monitoring, or a related technical discipline.
• Experience working with observability and monitoring platforms such as Datadog, Dynatrace, Catchpoint, Akamai mPulse, New Relic, or similar tools.
• Strong understanding of Core Web Vitals including LCP, INP, and CLS, as well as browser performance metrics such as TTFB, FCP, and Speed Index.
• Working knowledge of modern web technologies including React, Next.js, server-side rendering, and API-driven architectures.
• Experience analyzing performance across browsers, devices, networks, APIs, and backend services.
• Understanding of CDN concepts, caching strategies, cache-control headers, and edge delivery optimization.
• Experience creating dashboards, alerts, reports, and performance monitoring solutions.
• Basic scripting and automation experience using JavaScript, Python, or similar languages.
• Strong troubleshooting, analytical, and problem-solving skills.
• Excellent verbal and written communication skills with the ability to present technical findings to both technical and non-technical audiences.

Preferred Qualifications

• Experience with Akamai CDN, EdgeWorkers, or other edge delivery platforms.
• Experience supporting Next.js applications and composable commerce architectures.
• Experience with Datadog APM, RUM, Logs, and Synthetic Monitoring.
• Experience with Catchpoint synthetic testing and performance automation.
• Familiarity with HarperDB or modern distributed data platforms.
• Experience integrating performance testing into CI/CD pipelines.
• Familiarity with BrowserStack, Selenium, Storybook, Lighthouse, or related testing frameworks.
• Experience supporting high-traffic e-commerce websites and digital customer experiences.
• Understanding of release validation, feature flagging, and performance governance practices.
• Understanding of emerging AI, LLM, and generative AI technologies and their impact on web performance, observability, scalability, and digital customer experiences.
• Familiarity with monitoring and analyzing AI-driven traffic, bot behavior, API consumption patterns, and AI-enabled applications.
• Experience leveraging AI-assisted capabilities within observability platforms to improve operational efficiency and accelerate issue detection and resolution.
• Knowledge of performance considerations related to AI-powered services, inference workloads, API integrations, and large-scale automated traffic patterns is a plus.

Ralph Lauren will consider for employment qualified applicants with arrest or conviction records in a manner consistent with the requirements of the law, including any applicable fair chance laws. Please note background checks will be evaluated individually.

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Ralph Lauren is dedicated to providing a comfortable and consciosusly inclusive work enviroment for everyone regardless of gender identity and expression, race, religion, national origin, sexual orientation, age, marital status, disability, or any other category protected by applicable law. If you are vision-impaired or have some disability under the Americans with Disabilities Act or a similar law, and you wish to discuss potential acommodations related to applying for employment at Ralph Lauren, please contact Global People Practices at globalpeoplepractices@ralphlauren.com

For all other application support inquiries, please contact rl-careersitehelp@ralphlauren.com

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