Lead architecture and development of a cloud-native, multi-tenant control plane. Design and scale distributed, event-driven systems and high-throughput backends, ensure performance and compliance, partner with data/ML teams, drive infrastructure strategy, mentor engineers, and guide long-term platform architecture.

Own the full lifecycle of production classification and detection models, including transformer fine-tuning, entity detection, behavioral risk scoring, training, serving, versioning, evaluation, drift detection, and retraining. Build SageMaker-based ML systems and define output contracts supporting audit and policy enforcement. Lead the evaluation harness and mentor a co-op while operating as the company’s sole ML engineer.