• Built a scalable Python microservice using asyncio, multithreading, and semaphore locks to enable 200+ concurrent ML predictions per minute, significantly reducing latency.

• Engineered event-driven backend workflows that improved overall system responsiveness by 60%, ensuring seamless concurrent API execution.

• Designed and optimized a high-volume ETL pipeline ingesting over 1 billion records into ClickHouse, reducing query latency by 50%.

• Achieved a 70% reduction in data processing time by optimizing batch insert operations, enabling 5x faster ingestion of over 10 million records per day.

• Automated CI/CD pipelines using GitHub Actions, integrated SonarQube for continuous code quality checks, and deployed Dockerized applications on AWS, reducing deployment time by 30% and achieving 99.9% uptime.

• Orchestrated the deployment of 10+ microservices on Azure AKS using NGINX Ingress controllers and Kubernetes network policies for secure traffic routing; integrated Azure Files and Azure MySQL for persistent, scalable storage.

• Developed an interactive chat interface supporting concurrent users, combining WebSockets for real-time updates and SSE streams for LLM-driven reasoning with chain-of-thought display; implemented asynchronous RESTful endpoints with thread-based concurrency and connection pooling, reducing database latency by 40% under load.

• Enhanced VisualVoiceMail performance by 40% and reduced code complexity by 20% through migration to MVVM and Kotlin.

• Implemented dual SIM support with 95% unit test coverage, reducing production bugs by 40%.

• Developed a machine learning model to detect high-risk app permissions, enhancing mobile user privacy.

• Developed motion detection algorithms using bandpass filters and step detection with accelerometer and gyroscope data to enhance accuracy in low-GPS environments.

• Improved IoT energy efficiency by implementing sensor-based room occupancy tracking, reducing reliance on GPS in low-signal areas.