Lead and scale a multidisciplinary engineering organization building real-time, AI-driven spatial computing applications. Define technical strategy, oversee architecture, ensure platform scalability and reliability, collaborate cross-functionally, and cultivate engineering culture and talent.

Build and maintain versioned, staged data pipelines that ingest and conflated complex retail and spatial data into high-fidelity, production-ready outputs. Implement pragmatic AI (LLMs + rules/regex) for entity resolution, ensure schema and pipeline versioning, and design cost-effective, scalable solutions for retail-scale datasets.

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.