The Principal Quality Engineering Solutions Engineer at ServiceNow will lead and deliver complex, high-impact cross-functional programs using formal TPM practices such as timeline planning, stakeholder coordination, and risk mitigation.
This role involves designing and implementing testing strategies for AI/ML models, focusing on model performance, fairness, data validation, and continuous monitoring.
The engineer will collaborate with Design, Engineering, and Product leaders to embed quality into all stages of the development lifecycle.
Continuous improvement will be driven by mentoring engineers, enhancing test frameworks, and promoting best practices in automation, tooling, and data-driven quality metrics.
The engineer will 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.
Requirements:
Candidates must have experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving.
A minimum of 15 years of experience in project/program management and quality engineering in mid-to-large organizations is required, ideally with exposure to design-led teams.
Experience in quality engineering architecture, test automation architecture, or software development is necessary, along with strong programming experience in Java, JavaScript, and Selenium WebDriver.
Deep familiarity with QE architecture, including test automation frameworks, CI/CD pipelines, and quality metrics is essential.
A strong understanding of enterprise network architecture, cloud platforms (AWS, Azure, GCP), and modern DevOps practices is required.
Candidates should have experience critically integrating AI into workflows, automation strategies, or decision-making.
Demonstrated success in leading cross-functional programs using formal TPM practices is necessary.
Hands-on experience testing AI/ML models, pipelines, and related data workflows is required.
Familiarity with ML frameworks like TensorFlow, scikit-learn, or PyTorch is preferred.
Candidates must be able to successfully architect, execute on, and evangelize vision and longer-term operational strategies in conjunction with cross-functional leadership.
Experience working on and managing large projects or programs with cross-functional teams is required.
A Bachelor's degree with 15 years of relevant experience, a Master's with 12 years, or a PhD with 8 years of relevant experience is necessary.
Benefits:
The position offers a base pay range of $217,500 - $380,700, plus equity (when applicable), variable/incentive compensation, and benefits.
Health plans are included, which feature flexible spending accounts, a 401(k) Plan with company match, and an Employee Stock Purchase Plan (ESPP).
The company provides matching donations, a flexible time away plan, and family leave programs.
Compensation is based on geographic location and is subject to change based on work location.
