Lead Software Quality Engineer

Atrius, part of Acuity Inc., creates cloud applications that collect, analyze, and mobilize data to improve building efficiency, sustainability, and navigation. The Lead Software Quality Engineer will provide technical leadership for Quality Engineering, develop quality strategies, improve testing and automation practices, identify systemic quality risks, and mentor the Quality Engineering team.

Responsibilities:

• Partner with software engineers, product, architecture, and other stakeholders to define effective quality strategies, identify risks, and build quality throughout the software development lifecycle
• Serve as a trusted Quality Engineering expert and coach, providing technical direction and helping teams make risk-based decisions on testing, automation, tooling, and quality practices
• Identify opportunities to improve engineering effectiveness through automation, tooling, testability, and process improvements, including automating complex integration and end-to-end scenarios where appropriate
• Proactively identify systemic quality risks and improvement opportunities, using data and quality signals to investigate problems and drive solutions to implementation
• Raise the technical capability of the Quality Engineering team through mentoring, technical guidance, reviews, knowledge sharing, and constructive feedback

Requirements:

• Bachelor's Degree or equivalent relevant work experience
• 5+ years of Quality Engineering experience defining quality strategies for complex, integrated software systems, including automation, integration, and end-to-end testing
• Strong programming or scripting experience with the ability to design, review, and guide test automation solutions
• Demonstrated experience leading technical initiatives and influencing decisions across engineering teams without direct authority
• Strong written and verbal communication skills, including the ability to communicate technical risks and recommendations to technical and non-technical audiences
• Experience with observability or production quality signals
• Experience with AI-assisted software development or quality engineering tools