Implement and operationalize QA architectures across mobile (Flutter, iOS, Android), web (front-end and browser-based), backend/API services, and IoT/connected device platforms, in alignment with standards set by the COE Solution Architecture leadership.
Translate reference architectures and COE patterns into concrete, working frameworks and tooling that engineering teams can adopt.
Lead the hands-on evaluation, configuration, and rollout of testing frameworks, tools, and platforms appropriate to each domain.
Apply established quality gates, entry/exit criteria, and risk-based testing strategies within SDLC and Agile delivery pipelines.
Collaborate with other QA Architects in the COE to ensure cohesive execution and consistent adoption across domains.
Mobile QA Implementation
Implement test automation solutions for Flutter-based and native mobile applications covering functional UI testing, device compatibility, network simulation, accessibility, offline behavior, and deep-link validation.
Configure and manage device farm solutions (e.g., BrowserStack App Automate, AWS Device Farm, Firebase Test Lab) in line with approved device coverage strategies.
Execute mobile performance testing approaches covering app launch time, frame rendering, memory profiling, and battery consumption.
Build and maintain automation using both Flutter's native testing stack (flutter_test, integration_test, widget testing) and Appium with Java as equally primary automation layers, selected based on test scope and coverage needs.
Implement mobile CI/CD pipeline integrations including build triggers, parallel execution, and results reporting.
Web QA Implementation
Implement test automation solutions for web applications covering functional UI, cross-browser compatibility, accessibility (WCAG), and responsive design validation.
Build and maintain web automation frameworks using Playwright as the primary tool, with modularity and CI/CD integration in mind.
Configure and manage BrowserStack Automate for cross-browser and cross-device web test execution, including parallel suite management within pipelines.
Apply visual regression testing practices for web using AI-assisted tools where directed.
Backend & API QA Implementation
Implement testing solutions for backend services including API contract testing, integration testing, data validation, and service virtualization.
Build and maintain API functional and contract testing implementations using Karate Framework or similar tools.
Implement backend performance and load testing using Gatling, including scenario design, threshold configuration, and CI/CD integration.
Execute approaches for database testing, message queue validation, and event-driven system verification.
Apply chaos engineering and fault injection patterns to validate backend resilience in alignment with COE guidance.
IoT & Connected Device QA Implementation
Implement QA solutions for IoT and connected device platforms — including onboard ship systems, crew-facing devices, and guest-facing hardware endpoints.
Execute test approaches covering firmware/software integration, connectivity and protocol testing (MQTT, BLE, Wi-Fi), device provisioning, and edge-case failure modes.
Apply hardware-in-the-loop (HIL) testing patterns and emulator/simulator strategies where physical device access is limited.
Work with embedded and platform engineering teams to integrate device testing into CI/CD workflows.
AI Adoption for QA
Drive hands-on adoption of AI-powered testing capabilities across all domains — including AI-assisted test generation, self-healing locators, ML-based visual regression, and intelligent test selection.
Configure and integrate AI/ML tools (e.g., Applitools, Mabl, Copilot-assisted scripting, LLM-based test generation) to increase team velocity and reduce test maintenance overhead.
Build workflows in which large language models (LLMs) augment QA engineers — such as automated requirement-to-test-case generation, defect pattern analysis, and test coverage gap identification.
Apply guardrails and evaluation criteria for AI-generated tests as established by COE leadership.
COE Enablement & Delivery
Contribute to QA COE framework documentation, onboarding materials, and runbooks to ensure adopted tooling and patterns are well-documented and repeatable.
Track and report on quality engineering KPIs: automation coverage, defect escape rate, test cycle time, flakiness index, and MTTR for test failures.
Participate in architecture reviews and provide hands-on technical guidance to QA engineers across NCLH teams.
Partner with DevOps/Platform Engineering to embed quality tooling into CI/CD pipelines (GitHub Actions, Jenkins, Azure DevOps, Fastlane, or similar).
Mentor mid-level QA engineers; contribute to communities of practice and internal enablement sessions.
Required Qualifications
7+ years of experience in software quality engineering, with at least 3+ years in a QA architecture or senior technical lead role.
Proven experience implementing automation frameworks across two or more of the following domains: mobile, web, backend/API, or IoT/connected devices.
Hands-on experience with Appium and Java for mobile test automation, including framework design, scripting, and maintenance.
Hands-on experience with Flutter testing — flutter_test, integration_test, and widget testing.
Experience with Playwright for web test automation and cross-browser testing strategies.
Hands-on experience with BrowserStack (App Automate and/or Automate) — configuring capabilities, running parallel test suites, and integrating with CI/CD pipelines.
Hands-on experience with Karate Framework for API functional and contract testing.
Hands-on experience with Gatling for backend performance and load testing, including scenario scripting and pipeline integration.
Familiarity with IoT or embedded systems testing concepts, connectivity protocols (MQTT, BLE), or device integration testing.
Strong understanding of CI/CD practices and experience integrating automated tests into pipelines (GitHub Actions, Jenkins, Azure DevOps, Fastlane, or similar).
Hands-on experience applying AI/ML tools or LLM-assisted workflows within a QA context.
Proficiency in Java and Dart; familiarity with at least one additional language (Python, Kotlin, Swift, or JavaScript/TypeScript).
Strong knowledge of Agile/SAFe delivery methodologies and quality engineering practices within agile teams.
Excellent written and verbal communication skills; able to contribute to and present technical documentation to engineering and non-technical stakeholders.
Preferred Qualifications
Experience in travel, hospitality, e-commerce, or consumer-facing applications with significant user-facing complexity.
Familiarity with performance and observability tools (Firebase Performance, Datadog, New Relic, k6, Gatling).
Experience with visual AI testing tools (Applitools Eyes, Percy).
Knowledge of security testing practices for mobile and web (OWASP Mobile Top 10, OWASP Web Top 10, static/dynamic analysis).
Experience with hardware-in-the-loop (HIL) testing or device farm management for IoT platforms.
Familiarity with app store deployment pipelines (App Store, Google Play) and release management.
ISTQB Advanced Level or equivalent certification.
Experience working within a QA Center of Excellence or similar shared services model.
What Makes You Stand Out
You are an implementer and an executor — you take architectural direction and turn it into working, well-crafted solutions that teams actually use.
You are fluent across platforms — you adapt testing approaches to the unique characteristics of each domain rather than forcing a one-size-fits-all framework.
You are a pragmatic adopter of AI — you've moved past the hype and know how to extract real productivity gains from AI tools across web, mobile, backend, and device testing.
You bring precision and speed — you write clean automation code, document what you build, and ship solutions that last.
You are a trusted technical partner — your peers and delivery teams rely on you to translate strategy into something that works in practice.
