Software Engineer with 8+ years of experience designing, building, and deploying highly scalable, customer-facing systems across platforms. Proven ability to lead complex projects from concept to launch, driving key business metrics in high-traffic environments.
Launched 5 high-visibility promotions driving 2M+ signups and led end-to-end implementation for new paid offer types (upfront payment, tiered pricing) across Amazon and third-party stores (iOS/Android).
•
Integrated the subscription cancellation flow with a CMS, empowering marketing to rapidly launch A/B experiments. This optimization directly contributed to 100k+ 'cancel saves'.
•
Replaced a complex legacy monolith by deploying a new, high-performance BFF microservice (RPC-based APIs) with its full CI/CD pipeline, ensuring data coherence across all voice and visual clients.
•
Served as a key launch contributor for the "FanQuest" acquisition game, implementing its dynamic content architecture and reward email system.
Replaced a critical streaming device limit error with an in-app upsell feature, driving 53k+ annualized upgrades to the Family Plan.
•
Engineered the 'Swipe to Signup' feature, adding intentionality to the mobile flow and significantly reducing Customer Service load from accidental signups.
•
Drove family plan adoption from 1.6 to 2.0+ members by revamping the 'Invite Family' page, replacing manual email entry with a shareable tiny URL and Prime Family import.
•
Owned the high-risk, critical upgrade of the core 'Horizonte' (Spring-based) framework, navigating 3-4 major versions of breaking changes to deliver a stable migration with zero regressions, eliminating security vulnerabilities and unblocking future development.
Developed Real-Time Video Analytics Pipeline for integrated computer vision algorithms with product dashboards using GCP and AWS for brand content tracking. Tracked celebrity occurrences and influencer presence to help brands optimize targeted advertising and sales conversion.
•
Created algorithms to detect and estimate demographics (age, gender, emotion) of faces in videos using Caffe, Keras, and TensorFlow, enabling diversity analysis for major brands.
