The Director of AI Engineering will lead our organization's artificial intelligence initiatives with a focus on applying cutting-edge AI and machine learning technologies to solve complex problems in the pharmaceutical industry. This strategic leadership position requires a visionary who can drive AI adoption, oversee capability development, and ensure successful integration of AI solutions across the organization. As a Director of AI Engineering, a typical day might include the following: Strategic Leadership Develop and execute a comprehensive AI roadmap aligned with business goals Identify key AI capabilities and prioritize projects based on business impact Collaborate with executives to translate business needs into actionable AI strategies Stay abreast of emerging AI technologies and trends, evaluating potential organizational impact Make strategic decisions on building versus acquiring AI capabilities to meet current and future business needs Technical Oversight Oversee architecture and design for scalable AI systems and deployment frameworks Provide technical guidance on AI model selection, optimization, and evaluation methodologies Ensure quality standards, best practices, and ethical considerations are integrated into AI development Guide AI development, model building, training, and implementation processes Team Management Lead and collaborate with a high-performing team of AI engineers, data scientists, and ML engineers Foster a culture of innovation and continuous learning Develop specialized AI talent within the organization Delegate tasks effectively, manage project timelines, and monitor team performance Project Execution Oversee the full AI lifecycle from data collection to model deployment and monitoring Collaborate with cross-functional teams to integrate AI solutions into existing systems Manage project budgets, resource allocation, and delivery timelines Ensure timely and successful implementation of AI initiatives AI Best Practices & Guidelines Establish organizational AI & Automation best practices and guidelines Ensure quality, security, and regulatory compliance in all AI initiatives Implement responsible AI principles throughout the development lifecycle