Role Overview

Build and scale an AI-native, automation-first Quality Engineering function that materially improves release velocity, reduces defect leakage, and enables real-time production quality monitoring across the commerce platform. The role is expected to transform quality from a downstream validation activity into an engineering-led quality system embedded across OMS, WMS, storefront, AI copilots, and third-party integrations—ensuring resilient, observable, and trusted customer experiences at scale.

Responsibilities

• Define and execute the long-term Quality Engineering strategy for the commerce and retail platform, with a strong emphasis on automation-first, shift-left, and AI-native testing practices.
• Lead end-to-end quality coverage across OMS, WMS, storefront, AI copilots, APIs, event streams, and integration surfaces, ensuring testability across distributed systems and microservices.
• Build, mentor, and retain a high-performing team of automation engineers and SDETs, setting technical standards and career development plans.
• Design and implement scalable automation frameworks using Playwright, Cypress, Selenium, API testing tools, and programming languages such as JavaScript, Python, or Java.
• Introduce AI-assisted testing capabilities including self-healing test frameworks, intelligent test selection, flaky test detection, and synthetic data generation for commerce scenarios.
• Own quality gates in CI/CD pipelines using GitHub Actions, Jenkins, and related tooling to ensure every release meets agreed standards for coverage, reliability, and risk reduction.
• Establish robust performance, load, stress, soak, and resilience testing practices using JMeter, k6, Locust, and production-like test environments.
• Define production observability and quality monitoring practices in partnership with platform and SRE teams using Grafana, Prometheus, Datadog, logs, traces, and alerting signals.
• Drive API contract validation, event-driven testing, integration verification, and regression automation for complex distributed commerce workflows.
• Partner with product, engineering, DevOps, and architecture teams to embed quality requirements early in design and development cycles.
• Measure and continuously improve key quality indicators such as automation coverage, defect leakage, escaped production issues, mean time to detect quality regressions, and release cycle duration.
• Champion a culture of engineering excellence, accountability, and continuous improvement, replacing manual-heavy QA practices with modern Quality Engineering principles.

Qualifications