Principal Quality Engineering Solutions Engineer

Principal Quality Engineering Solutions Engineer

Requirements

• Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry.
• 15+ years of experience in project/program management and quality engineering in mid-to-large organizations, ideally with exposure to design-led teams.
• Experience in quality engineering architecture, test automation architecture, or software development. Strong programming experience with Java, JavaScript, and Selenium WebDriver.
• Deep familiarity with QE architecture including test automation frameworks, CI/CD pipelines, and quality metrics
• Strong understanding of enterprise network architecture, cloud platforms (AWS, Azure, GCP), and modern DevOps practices.
• Experience critically integrating AI into workflows, automation strategies, or decision-making—such as leveraging LLMs, predictive analytics, or AI-powered test automation tools
• Demonstrated success in leading cross-functional programs using formal TPM practices (timeline planning, stakeholder coordination, risk tracking, etc.).
• Hands-on experience testing AI/ML models, pipelines, and related data workflows.
• Familiarity with ML frameworks like TensorFlow, scikit-learn, or PyTorch.
• Is able to successfully architect, execute on and evangelize vision and longer-term operational strategies in conjunction with cross-functional leadership.
• Relies on experience, wealth of industry knowledge and trends to proactively champion future possibilities and directions to leadership.
• Educates senior leaders across the company about their discipline and its value, and advises on current trends and future possibilities with the goal of advancing the industry through contributions to trade events and publications.
• Experience working on and managing large projects or programs with cross-functional teams. Deliver solutions and strategies while mitigating or removing obstacles.
• Experience utilizing software to keep projects organized, track metrics, and report on progress.
• A Bachelor’s degree with 15 years of relevant experience, or 12 years with a Master’s, or 8 years with a PhD—or equivalent experience.

Responsibilities

• Lead and deliver complex, high-impact cross-functional programs using formal TPM practices (e.g., timeline planning, stakeholder coordination, risk mitigation).
• Design and implement testing strategies for AI/ML models, including model performance, fairness, data validation, and continuous monitoring.
• Collaborate with Design, Engineering, and Product leaders to embed quality into all stages of the development lifecycle.
• Drive continuous improvement by mentoring engineers, enhancing test frameworks, and promoting best practices in automation, tooling, and data-driven quality metrics.
• Act as a strategic advisor and thought leader across the organization, helping shape the long-term Quality Engineering vision and aligning it with emerging industry trends and technologies.

Preferred Qualifications

No preferred qualifications provided.