Senior Principal AI Architect, Workday

• 15+ years of progressive experience in data and analytics, with a significant and demonstrable track record of architecting and delivering highly complex AI/ML solutions at enterprise scale (with AI infrastructure, application deployment and operations taken into consideration)
• 7+ years experience with advanced machine learning algorithms, statistical modeling techniques, deep learning architectures, natural language processing (NLP), and other cutting-edge AI methodologies
• 7+ year experience with architecting solutions on cloud-based data platforms, with mastery of Snowflake and Databricks and a strong understanding of their advanced features and capabilities for AI/ML workloads
• Bachelor's or Master's degree (PhD preferred) in Computer Science, Data Science, Artificial Intelligence, or a related field
• Proven ability to architect and oversee the implementation of highly scalable, resilient, and secure data pipelines and end-to-end MLOps workflows for deploying and managing AI models in production environments at scale
• Comprehensive understanding of enterprise data governance frameworks, security architectures, ethical considerations in AI, and regulatory compliance requirements relevant to AI systems
• Exceptional communication, presentation, and influencing skills, with the proven ability to articulate complex technical visions and strategies to executive leadership and diverse audiences
• Demonstrated ability to lead, inspire, and influence senior technical leaders and cross-functional teams across a large organization
• Extensive experience with advanced MLOps platforms and practices for automating, monitoring, and governing the AI lifecycle at scale
• Significant experience in a SaaS environment, with a strong understanding of the unique architectural challenges and considerations

Desirable

• Workday is seeking a Senior Principal AI Architect within EDATA who will be a recognized thought leader and a driving force in shaping and executing our enterprise-wide Artificial Intelligence (AI) strategy
• You will partner with executive leadership, Platform Engineering, Data Science, Data Engineering, AI Product Management, and key business stakeholders to define the long-term architectural vision for AI, spearheading the design and implementation of highly complex, scalable, secure, and impactful AI solutions leveraging our extensive data assets and advanced platforms
• Visionary Leadership: Define and evangelize the long-term AI architectural vision, strategy, and roadmap for Workday, proactively anticipating future needs and aligning with executive business priorities and the broader technology landscape
• Enterprise-Scale Solution Architecture: Architect highly complex, enterprise-grade AI solutions, including advanced machine learning models, sophisticated natural language processing (NLP) systems, agentic capabilities, and innovative AI technologies, ensuring unparalleled scalability, performance, resilience, and security
• Deep Platform Integration Strategy: Define the strategic direction for the seamless and optimized integration of AI solutions with our core data platforms (Snowflake and Databricks), establishing architectural patterns and guidelines for leveraging their advanced capabilities
• Emerging Technology Foresight: Proactively research, evaluate, and strategically recommend disruptive and emerging AI technologies, tools, and frameworks, positioning Workday as an industry leader in AI innovation
• Architectural Governance and Standards: Establish and govern enterprise-wide architectural principles, patterns, and best practices for the full lifecycle of AI solution development and deployment within EDATA, ensuring consistency, quality, and maintainability
• Executive Collaboration and Influence: Collaborate strategically and influence executive leadership, Data Science and Engineering leadership, and key business stakeholders to drive alignment on the AI architectural vision, advocate for strategic investments, and ensure successful adoption of AI initiatives
• Risk Management and Compliance Architecture: Define and implement robust architectural frameworks to proactively address data governance, security, ethical considerations, and regulatory compliance requirements for AI systems at an enterprise scale
• Performance Engineering and Optimization Strategy: Lead the development of strategic approaches for identifying and resolving critical architectural bottlenecks and performance limitations in complex AI systems, ensuring optimal resource utilization and exceptional user experiences for AI-powered products and services
• Technical Mentorship and Talent Development: Provide strategic technical leadership, mentorship, and guidance to Principal Architects, architects, and engineering leaders across the organization, fostering a culture of technical excellence and developing future AI architectural talent
• Strategic Innovation and Incubation: Drive strategic innovation by identifying and championing transformative AI use cases and technologies, leading high-impact proof-of-concept initiatives and incubating new AI capabilities with significant potential for business disruption and growth