Principal- Quality Engineering

United Airlines•Chicago, IL

8d•$140,600 - $191,620

About The Position

Achieving our goals starts with supporting yours. Grow your career, access top-tier health and wellness benefits, build lasting connections with your team and our customers, and travel the world using our extensive route network. Come join us to create what’s next. Let’s define tomorrow, together. United's Digital Technology team is comprised of many talented individuals all working together with cutting-edge technology to build the best airline in the history of aviation. Our team designs, develops and maintains massively scaling technology solutions brought to life with innovative architectures, data analytics, and digital solutions.

Requirements

Bachelor's degree in Computer Science, Engineering, Business Administration, or related field
5+ years of management experience in Quality Engineering or IT leadership related role
5+ years of experience implementing Test Automation frameworks
5+ years of experience in supporting release automation (CICD) and application performance testing
Strong project organizations skill, including prioritization, planning and organization
Experience with cloud, distributed, microservice, mainframe and desk top based technology
Understanding of AI-driven innovation and deployment of Agentic AI solutions for Autonomous test execution, Intelligent defect triage, risk prediction and Test prioritization
Experience in application development and testing, multiple major projects delivering of med-large scale projects/programs
Strong Programming Skills: Java, Selenium, Python or SQL
Must be legally authorized to work in the United States for any employer without sponsorship
Successful completion of interview required to meet job qualification
Reliable, punctual attendance is an essential function of the position

Nice To Haves

Master's degree
TMMI (Test Maturity Model Integration) Certification and/or knowledge
CSTE or any other Test Automation related certifications
5 – 10 years of experience in an Quality Engineering technical leadership related role
Experience in architecting the AI automation framework for UI, system interactions, agent flows, and multimodal input/output validation
Experience working with telemetry, logs, and debugging across large-scale systems
Experience with AWS
Experience in travel industry, especially airline related is a significant plus
Strong experience performing duties related to software quality engineering and design of automated solutions to automatically validate software builds to a variety of technologies
Experience with AI-driven innovation and deployment of Agentic AI solutions for Autonomous test execution, Intelligent defect triage, risk prediction and Test prioritization
Experienced in designing scalable automation frameworks and robust test data architectures with enterprise-grade software production code
Experience required in multiple technical platforms, operating systems, databases and development languages including but not limited to web, mobile, mainframe, cloud
Experience working within a multi-disciplined, cross-functional technical organization with matrixes reporting relationship
Strong oral and written communication skills

Responsibilities

Define and lead the enterprise technical strategy, architecture, standards, and roadmap for Quality Engineering, Automation, and Agentic Testing capabilities
Design and implement scalable automation frameworks and AI-powered quality platforms that improve software quality, engineering productivity, and delivery efficiency
Drive the adoption of Agentic Quality Engineering practices, including autonomous test generation, intelligent test execution, self-healing automation, and AI-assisted defect analysis to improve efficiency, coverage, and delivery speed
Establish governance, engineering standards, and best practices for automation, AI-enabled testing, quality intelligence, and continuous testing solutions
Partner with Engineering, Product, Platform, Security, DevOps, and Data teams to embed quality, automation, and observability throughout the SDLC, defining modern quality gates with high standards for engineering excellence
Leverage quality analytics, observability, production telemetry, and predictive models to identify risks, optimize testing strategies, leveraging quality metrics, AI effectiveness measures, operational KPIs, and customer outcomes to continuously improve software reliability and engineering efficiency
Lead innovation initiatives, evaluate emerging technologies, mentor engineering teams, and influence enterprise-wide quality transformation and automation maturity to build a state-of-the-art AI-enhanced quality engineering culture