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Job Summary:
Ralph Lauren Corporation is a global leader in the design and distribution of premium lifestyle products. They are seeking a Performance Engineer (Analyst) to optimize and improve their digital commerce platform, focusing on performance monitoring and enhancing customer experiences through AI and observability tools.
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.
Qualifications:
Required:
• 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:
• 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.
Company:
Ralph Lauren Corporation focuses on the design, marketing, and distribution of luxury lifestyle products. Founded in 1967, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.