Principal Data Ai Enterprise Architect

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ServiceNow

📍Remote - United States

Job highlights

Summary

Join ServiceNow as a Principal Data & AI Enterprise Architect, a senior leadership role responsible for defining, designing, and driving the data and artificial intelligence (AI) architecture across the enterprise. You will ensure strategic alignment of data, AI, and machine learning 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. You will collaborate with cross-functional teams to integrate AI-driven solutions that enhance decision-making, operational efficiency, and customer experience. The position demands extensive experience in enterprise architecture, data architecture, or AI/ML architecture, along with strong technical knowledge of AI, machine learning algorithms, and data science techniques. You will lead and develop enterprise-wide data and AI architecture strategy, design and implement data and AI frameworks, and collaborate with various teams to deliver AI-driven solutions.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or related equivalent 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
  • 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

Responsibilities

  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

Preferred Qualifications

  • Master’s or Ph.D. in AI, Machine Learning, Data Science, or related fields
  • ServiceNow certifications (e.g., Certified ServiceNow Architect)
  • Knowledge about ServiceNow AI capabilities

Benefits

  • Remote work options
  • Flexible work options

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