Leading end-to-end backend architecture of the Smart Ring platform, owning system design, data models, API contracts, processing workflows, and delivery timelines. Technically leading a backend team of three engineers, coordinating with the frontend/mobile lead on architecture changes, API contracts, release priorities, and integration trade-offs. Architected a worker-based distributed system using Node.js, TypeScript, BullMQ, Redis, MongoDB, MySQL, and Azure to ingest, process, and serve wearable telemetry across health modules. Built ring-processing workers that transform raw device sync data into chart-ready payloads, derived metrics, and AI-ready health context for the GoodFlip mobile application. Established async job processing patterns including retries, Redis-backed coordination, distributed locking, and cache warming to improve reliability of long-running worker flows. Investigated production worker reliability via profiling, log analysis, and query review; identified optimization areas across raw-data processing, payload composition, and retention-heavy flows. Defined REST API response models and contracts consumed by React Native clients for device onboarding, daily summaries, module charts, vital details, and health-insight experiences. Contributed to Kaira, GoodFlip's AI-powered healthcare assistant, and led design of the Smart Ring memory layer for persistent, context-aware AI experiences from wearable health data. Supported AI-powered CGM systems with doctor-approved insights, glucose spike detection, MongoDB time-series data, and background sync flows running every three minutes. Conduct PR reviews and architecture decisions, mentor backend developers, and collaborate with product, QA, frontend, and engineering leadership to ship production-ready healthcare systems.