Principal Data/AI Enterprise Architect
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Job Details
At ServiceNow, our technology makes the world work for everyone, and our people make it possible. We move fast because the world can’t wait, and we innovate in ways no one else can for our customers and communities. By joining ServiceNow, you are part of an ambitious team of change makers who have a restless curiosity and a drive for ingenuity. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible. We dream big together, supporting each other to make our individual and collective dreams come true. The future is ours, and it starts with you.
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Job DescriptionAbout Digital Technology:
We’re not yesterday’s IT department, we're Digital Technology. The world around us keeps changing and so do we. We’re redefining what it means to be IT with a mindset centered on transformation, experience, AI-driven automation, innovation, and growth.
We’re all about delivering delightful, secure customer and employee experiences that accelerate ServiceNow’s journey to become the defining enterprise software company of the 21st century. And we love co-creating, using, and highlighting our own products to do it.
Ultimately, we strive to make the world work better for our employees and customers when you work in ServiceNow Digital Technology, you work for them.
Job Overview
The Principal Data & AI Enterprise Architect is a senior leadership role responsible for defining, designing, and driving the data and artificial intelligence (AI) architecture across the enterprise. This role ensures the strategic alignment of data, AI, and machine learning (ML) initiatives with business goals, focusing on scalability, security, and innovation. This role requires a visionary leader who can bridge the gap between business needs and technical capabilities. The Principal Architect will collaborate with cross-functional teams to integrate AI-driven solutions that enhance decision-making, operational efficiency, and customer experience.
Key Responsibilities
- Enterprise Data & AI Strategy:
- Develop and lead the enterprise-wide data and AI architecture strategy, ensuring alignment with business objectives.
- Identify opportunities to leverage AI and machine learning technologies to optimize business processes and outcomes.
- Drive the adoption of emerging technologies in AI, machine learning, and data analytics to keep the organization ahead of technological trends.
- Architectural Design & Oversight:
- Design and implement data and AI frameworks, ensuring scalability, security, and efficiency.
- Provide architectural oversight for AI/ML projects, including platform selection, model development, deployment, and integration.
- Ensure best practices in data governance, AI ethics, privacy, and compliance are maintained.
- Collaboration & Leadership:
- Collaborate with business leaders, data scientists, data engineers, and software development teams to define and deliver AI-driven solutions.
- Guide teams in adopting new AI technologies, platforms, and methodologies.
- Present complex AI strategies and roadmaps to executive leadership, articulating the value and potential impact on the business.
- Innovation & Research:
- Stay up to date with the latest advancements in AI, machine learning, and data analytics technologies.
- Lead R&D initiatives to evaluate new tools, platforms, and techniques that can enhance the organization’s data and AI capabilities.
- Drive innovation in the application of AI for predictive analytics, automation, and operational intelligence.
- Governance & Compliance:
- Establish and enforce AI governance policies to ensure ethical AI use, transparency, and accountability.
- Ensure all data and AI architectures comply with regulatory and security requirements, including GDPR, CCPA, and other data privacy laws.
- Performance Monitoring & Optimization:
- Define key performance metrics (KPIs) for AI systems and solutions.
- Monitor AI models for performance, accuracy, and fairness, making recommendations for improvement.
- Ensure the AI models are explainable, reproducible, and maintainable.
Required Qualifications
- Education:
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or related equivalent experience
- Master’s or Ph.D. in AI, Machine Learning, Data Science, or related fields is preferred.
- Experience:
- 10+ years of experience in enterprise architecture, data architecture, or AI/ML architecture roles.
- Proven experience in leading large-scale AI and machine learning initiatives in a complex enterprise environment.
- Extensive experience with AI platforms, cloud-based data architectures, and machine learning frameworks
- Skills:
- Strong technical knowledge of AI, machine learning algorithms, and data science techniques.
- Expertise in data management technologies, including data lakes, data warehouses, ETL processes, and big data platforms.
- Familiarity with AI/ML model deployment and monitoring tools (MLOps).
- Excellent communication and leadership skills, with the ability to articulate AI solutions to both technical and non-technical stakeholders.
- Knowledge of AI governance, ethics, and data privacy regulations
Desired Qualifications
- ServiceNow certifications (e.g., Certified ServiceNow Architect) are highly desirable.
- Knowledge about ServiceNow AI capabilities
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Additional InformationServiceNow is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status or any other category protected by law.
All new employees hired in the United States are required to be fully vaccinated against COVID-19, subject to such exceptions as required by law. If hired, you will be required to submit proof of full vaccination or have an approved accommodation, by your start date. Visit our Candidate FAQ page to learn more.
If you require a reasonable accommodation to complete any part of the application process, or are limited in the ability or unable to access or use this online application process and need an alternative method for applying, you may contact us at talent.acquisition@servicenow.com for assistance.
For positions requiring access to technical data subject to export control regulations, including Export Administration Regulations (EAR), ServiceNow may have to obtain export licensing approval from the U.S. Government for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by the U.S. Government.
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Work personas
Work personas are categories that are assigned to employees depending on the nature of their work. Employees will fall into one of three categories: Remote, Flexible or Required in Office.
Required in Office
A required in office work persona is defined as an employee who is contracted to work from or aligned to a ServiceNow-affiliated office. This persona is required to work from their assigned workplace location 100% of the work week based on the business needs of their role.
Flexible
A flexible work persona is defined as an employee who is contracted to work from or aligned to a ServiceNow-affiliated office and will work from their assigned workplace location roughly 3 days/week or less (generally around 40-60% of the work week). Flexible employees may choose to work the remaining working time from their workplace location or home. Flexible employees are required to work within their state, province, region, or country of employment.
Remote
A remote work persona is defined as an employee who performs their responsibilities exclusively outside of a ServiceNow workplace and is not contracted or aligned to a ServiceNow-affiliated office, including those whose place of work (pursuant to their terms and conditions of employment) is their home. Remote employees are required to work within their state, province, region, or country of employment.
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