Analyze and document business requirements for AI-driven solutions, ensuring an understanding of the problem space and desired outcomes.
Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics).
Collaborate with data science and data engineering teams to identify, clean, and structure the necessary supply chain data for use in ML and agent models.
Partner closely with supply chain operations, architects, finance, and engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production.
Lead, mentor, and grow a technical program management team, fostering high performance and collaboration. Manage hiring, performance, career development, and resource allocation.
Minimum qualifications:
Bachelor's degree in Computer Science, Engineering, Mathematics, Operations Research, a related quantitative field, or equivalent practical experience.
8 years of experience in global supply chain operations, planning, or logistics, within the enterprise hardware or cloud infrastructure space.
5 years of experience in leadership roles with/without direct reports.
Experience with prompt engineering and classical ML solutions, predictive modeling, or deep learning solutions.
Experience working with generative AI, integrating genAI solutions into business processes, and agent-based modeling.
Preferred qualifications:
5 years of experience in developing and deploying machine learning models or AI-driven applications.
Experience working in Java and Python.
Experience with standard API design and system architectures.
Familiarity with data science libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow/PyTorch).
