Architected scalable side effects system managing transient database tasks with cron-based execution engine, supporting immediate/delayed actions with team-configurable monitoring; adopted by 10+ product teams with 20+ registered side effects to orchestrate feature access changes on access-based events.

Created enterprise-scale free trial infrastructure with Django APIs serving 4 products, handling 1M+ requests/sec and 50k+ concurrent users with Redis ElastiCache and Aurora RDS, contributing to a 15% conversion rate lift and accelerating sales acquisition.

Built scalable usage threshold and payment notification system with a config-driven approach, eliminating existing product-specific boilerplate classes and reducing code maintenance overhead while providing automated notifications for payment success/failure events and usage threshold limits reached across products.

Designed and deployed a real-time Stripe webhook processing system with automated billing plan discrepancy detection and distributed tracing, eliminating plan mismatches and reducing incident resolution time by 50%.

Scaled billing Memcached infrastructure and implemented Splunk cron job monitoring alerts to maintain 100% billing uptime during 5x Black Friday traffic surge.

Delivered UK VAT compliance system within critical Black Friday/Cyber Monday deadline, enabling significant monthly revenue expansion.

Extended ML deployment infrastructure for Embark's dog DNA testing product by implementing Apache Airflow workflows for new ML models including the productionized Mast Cell Tumor (MCT) ML model, processing 120K+ genetic assessments/month and ~6k DNA samples/day with 99.99% uptime.

Led productionization of Embark's Dog Age Test by researching scientific literature and recommending preprocessing optimizations to scientists, then transforming experimental Jupyter notebooks into a production Python package using NumPy vectorized operations on DNA methylation data, reducing ML feature deployment time from months to weeks following scientific advisory board review.

Designed domain-driven PostgreSQL schemas for Illumina sequencing workflows, improving data consistency by 30% and enabling cross-functional genetic research at scale.

Partnered with 10+ veterinarians and geneticists to validate and release health and trait algorithms, expanding available genetic insights to 250+ total while ensuring accurate genome data storage and UI presentation.

Architected and co-owned critical microservices integrating Apple's Volume Purchase Program API, managing license counts in CosmosDB to streamline app deployment and license management worldwide.

Led deprecation and removal of an outdated data provider, saving a DB migration and reducing codebase complexity and enhancing maintainability for the engineering team.

Architected scalable distributed ML training infrastructure on Azure Batch AI using Keras, TensorFlow, and Horovod, enabling multi-node model training for satellite image classification processing thousands of images identifying sustainable farming practices.

Designed and implemented an advanced signal processing pipeline in R for clinical research (Project Fizzyo), developing a custom peak detection algorithm that improved pattern analysis accuracy for cystic fibrosis treatment optimization.

Delivered React-based administrative dashboard for Fortis, a UN crisis response platform, enabling real-time sentiment analysis and media aggregation across multiple channels during humanitarian emergencies.