SUMANTH KONJETI

Engineered a high-throughput ML pipeline with EDA on HPC clusters to analyze 7,000+ protein markers using linear mixed models. Boosted biomarker identification by 30% in Alzheimer's research through scalable statistical modeling.

Designed and deployed a cloud-native backend using Django REST and AWS Lambda, orchestrated via API Gateway.

This architecture reduced latency by 20% and enabled 5+ service integrations to support over 10K users seamlessly.

Built the full-stack architecture for "MyYouthSpan", developing health-tracking modules with reusable React components, Django logic, and ML inference-boosting system reliability by 20% and engagement by 40%.

Implemented HIPAA-compliant authentication using AWS Cognito, JWT roles, cutting security incidents by 20%.

Orchestrated dockerized ML models to SageMaker, enabling real-time inference & cutting prediction latency by 50%.

Engineered event-driven microservices using Spring Boot and Kafka, optimizing async messaging for core V3 Services and significantly improving delivery effectiveness by 30%, streamlining communication for 10+ enterprise clients.

Designed modular, reusable backend components using SOLID OOP principles, boosting feature delivery by 30%.

Automated deployments with cron jobs, bash scripts, and CI/CD pipelines, eliminating 70% of manual work.

Integrated ELK Stack integration for [24]7.ai Assist during the GCP migration, enabling centralized logging and monitoring. Reduced latency by 50% and improved system reliability by 15% through enhanced observability.

Led performance stress testing (PSR) for [24]7.ai Assist, an AI-powered chatbot platform-simulating Black Friday/Cyber Monday traffic for BestBuy, CapitalOne to identify bottlenecks and strengthen deployment stability.