01Responsibilities
Enterprise AI StrategyDefine and execute the enterprise AI strategy and multi year roadmap, leveraging advancements in Generative AI, LLMs, multimodal AI, Agentic AI, data platforms, and cloud technologies to drive innovation, adoption, and measurable business outcomesLead the evolution of Enterprise AI across strategy, architecture, engineering, product management, platform capabilities, research, and value realization to deliver sustained enterprise impactOwn a portfolio of enterprise AI capabilities spanning internally developed solutions and strategic platforms such as Microsoft Copilot, Google AgentSpace, and emerging AI technologiesEstablish and scale the AI operating model, governance, and delivery frameworks that enable responsible, secure, and efficient adoption of AI across the enterprisePartner across Enterprise AI, Digital, Data, Infrastructure, Security, and Architecture organizations to drive strategic alignment, platform interoperability, technology standards, and capability reuseChampion enterprise-wide AI transformation by identifying high-value opportunities, accelerating adoption, and embedding AI-powered products, copilots, intelligent workflows, and agent-based systems into business operationsLead world-class AI engineering capabilities, with expertise in data engineering, analytics, modern data platforms, and enterprise-scale AI delivery to ensure operational excellence and business value realizationCorporate Systems Solution Strategy & ArchitectureReimagine and drive enterprise AI solution strategy that enables intelligent automation and transforms business operations across corporate functionsTranslate business and technology roadmaps into scalable AI-enabled solutions that accelerate enterprise transformationInfluence business and technology partners to modernize enterprise platforms into AI-ready architectures while maximizing the value of AI capabilities embedded within enterprise software platformsDrive innovation by defining scalable solution architectures that emphasize reuse, interoperability, security, and long-term maintainabilityPartner with enterprise architecture, engineering, and product organizations to ensure solution designs align with enterprise standards and strategic prioritiesDevelop reusable reference architectures, design patterns, and integration frameworks that accelerate delivery across multiple business domainsTechnical Delivery LeadershipLead engineering organizations responsible for delivering enterprise AI platforms and AI-powered business capabilities across the enterpriseEstablish engineering excellence through modern AI engineering practices, including DevOps, MLOps, and LLMOps, leveraging CI/CD, scalable architecture, Infrastructure as Code, containerization, observability, model .
