1. Led the design and development of a fully in-house promotion engine, replacing an expensive third-party application and reducing revenue expenditure by 72%.
2. Reduced API latency and cut database reads by 40% by caching user authorization/identity metadata in Redis (RBAC + user context lookups).
3. Improved concurrency and runtime efficiency by migrating 33% of core Python microservices to Go using Gin and gRPC, including rewriting handlers and updating service workflows.
4. Improved scalability under load by introducing NATS/RabbitMQ-based asynchronous workers that offloaded notifications and event processing from the main request path.
5. Improved service-level observability by integrating Jaeger-based distributed tracing and Sentry monitoring across microservices, enabling clearer end-to-end request flows.
