Provide proactive administrative, scheduling, travel, communication, and operational support to the CEO. Manage complex calendars, meetings, board and investor coordination, itineraries, briefing materials, confidential information, expenses, and initiative tracking. Serve as a liaison with internal and external stakeholders, support NYC office logistics, and improve executive-team processes while anticipating needs and maintaining accountability across priorities.

Own and build the data foundation for an AI sports-performance platform: design data architecture, real-time streaming ingestion, time-series storage, feature store and millisecond feature serving, sport knowledge graph and evaluation/calibration frameworks, ensure tenant-level isolation and provenance, and work closely with domain scientists and AI engineers to deliver trustworthy, production-grade ML infrastructure.

Design and ship reliable production agentic AI systems for sports performance. Build multi-agent orchestration, persistent memory, tool use, confidence calibration, human-in-the-loop escalation, evaluation harnesses, observability, and regression testing. Collaborate with sport scientists and domain experts to create grounded, traceable, actionable recommendations that appropriately defer to humans. Requires strong Python, software engineering, production operations, and hands-on experience with agentic AI, multi-agent systems, and probabilistic model calibration.