Senior QA Engineer

The AES Group•Phoenix, AZ

4d•Onsite

About The Position

We're looking for a Quality Engineer to help build and scale high-quality web experiences used by tens of millions of Card Members around the world. This role is ideal for an engineer who brings strong automation skills, a quality-first mindset, coding expertise, and a passion for solving complex problems in modern web environments. You'll be part of the Web Engineering team, which builds digital products and platforms that shape key moments across the customer journey. As a Quality Engineer, you will help ensure these experiences are reliable, scalable, and seamless by partnering closely with engineers, product teams, and platform teams throughout the development lifecycle. You'll work in a fast-paced engineering environment with the scale and stability of a Fortune 100 company. We're looking for someone who is comfortable navigating ambiguity, iterating quickly, and applying automation-first quality engineering practices to improve release confidence, accelerate feedback, and support continuous delivery. Familiarity with AI-assisted engineering tools and practices is a plus.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical discipline, with 10+ years of experience in a software engineering or quality engineering organization.
Hands-on experience designing and maintaining automated tests for web applications using tools such as Playwright and Selenium.
Hands-on experience building automated API tests using frameworks such as Playwright or equivalent API automation tools.
Strong working knowledge of JavaScript and familiarity with Java-based testing frameworks and modern test automation patterns.
Strong coding/programming experience with the ability to develop and maintain automation frameworks and test solutions.
Exposure to distributed systems, service-oriented architectures, and dependent system integrations in modern engineering environments.
Strong analytical, problem-solving, and communication skills, with the ability to work effectively across engineering, product, and platform teams.
Comfort working through ambiguity, thinking abstractly, and iterating quickly in a collaborative agile environment.
Demonstrated interest in automation-first quality engineering practices, including maintainable test design, CI/CD quality gates, and continuous improvement.
Experience implementing or applying AI-assisted engineering/testing strategies and tools, particularly to improve test design, accelerate troubleshooting, and enhance engineering productivity.

Nice To Haves

Experience in the financial services industry is a plus.

Responsibilities

Contribute as an active member of an agile engineering team by shaping user stories, defining acceptance criteria, and designing risk-based test scenarios that improve release confidence and product quality.
Build, maintain, and continuously improve automated test suites for web and API layers, with strong integration into continuous integration and delivery pipelines.
Drive an automation-first quality engineering approach by identifying opportunities to reduce manual effort, improve test reliability, and accelerate feedback throughout the development lifecycle.
Partner closely with product, frontend, backend, and platform engineers to validate requirements, prevent defects early, and deliver high-quality customer experiences.
Work alongside developers during feature implementation to enable shift-left testing, rapid iteration, and earlier detection of quality issues.
Develop and use service virtualization, mocks, and test data strategies to validate functionality efficiently across dependent systems.
Contribute to estimation, test strategy, and feasibility assessments by identifying quality risks, automation needs, and dependencies early in the planning process.
Promote consistent engineering and quality best practices across the team, including test maintainability, CI health, observability, and continuous improvement.
Apply analytical thinking and data-driven problem solving to improve coverage, identify gaps, and strengthen overall engineering quality.
Apply AI-assisted engineering practices and tools to improve test design, accelerate analysis, troubleshoot issues, and enhance quality engineering productivity.