Principal Data/AI Enterprise Architect, ServiceNow

• 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
• 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
• 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

Desirable

• 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
• 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