Architected distributed, event-driven data streaming pipelines handling 4.3M high-velocity messages daily (50 TPS) using Apache Kafka, optimizing partition strategies to guarantee zero data drop and 99.99% system uptime. Leveraged Python, LangChain, and RAG architectures to design agentic artificial intelligence workflows, embedding semantic and keyword text search models. Engineered containerized cloud infrastructure on AWS (EC2, S3, RDS) automated via Terraform scripts, successfully slashing infrastructure overhead by ~30%. Optimized microservice application performance by introducing Virtual Threads and ZGC memory tuning, eliminating garbage collection pauses by 30% for real-time processing.

Designed a dynamic runtime PII data-masking engine by manipulating structural backend log modules, successfully reducing redundant logic processing overhead by 50% across global microservices. Managed robust time-series observability frameworks (Prometheus, Grafana, Splunk) to monitor stream reliability, lowering Mean Time to Resolution (MTTR) across multi-tenant enterprise clusters. Developed modular UI components using Angular to streamline operational telemetry dashboards for system administrators.

Engineered core transactional ingestion components using Spring Boot to cleanly process over 500K daily high-integrity data payloads. Integrated Hazelcast distributed caching layers to flatten unexpected volume surges, stabilizing system latency spikes and strengthening database uptime by 12%. Optimized relational database schemas (MySQL) to maintain consistent query responsiveness against rapidly increasing structured transaction volumes.