• Own the architecture and evolution of our large-scale data extraction and normalization platform • Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability • Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards • Establish clear system contracts for correctness, traceability, and confidence (e.g., "where did this number come from?") • Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity • Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary • Partner with product and downstream consumers to define quality bars, SLAs, and success metrics • Serve as a technical escalation point for production issues, reliability failures, and systemic risks • Mentor senior engineers, shape technical culture, and raise expectations for system design and execution • Contribute to long-term technical strategy while remaining hands-on with critical implementations