Sai Mahit Vudi is a Cloud-Native Data Platform Engineer with over nine years of experience designing, developing, and optimizing enterprise-scale data platforms and high-throughput service infrastructure. He currently serves as a Lead Engineer at Fidelity Investments (contractor via Themesoft Inc.), where he architected the distributed caching layer, configurable canary routing infrastructure, and RushHour load-testing methodology powering a customer-facing enrichment API sustaining 6,000 RPS at P95 ≤ 80 ms latency in regulated financial services.
His technical focus centers on cloud-native distributed data platforms on AWS, high-throughput synchronous service infrastructure at SLA-bound scale, and machine learning operationalization at enterprise scale. He has extensive expertise with Apache Spark, PySpark, Hadoop, Airflow, NiFi, Databricks, Spring Boot, Kubernetes and AWS EKS, OpenTelemetry-based observability, and Infrastructure-as-Code with Terraform.
Across prior engagements with Nike (via Populus Group) and Novartis (via Soft Standard Solutions), Sai led machine learning operationalization work migrating R and Python data-science models into PySpark and H2O AI at enterprise scale and owned production Hadoop-on-AWS infrastructure in regulated pharmaceutical contexts. His experience spans financial services, healthcare, and retail, with particular emphasis on production data platforms serving customer-facing digital surfaces at Fortune-100 scale.
Sai speaks and writes on cloud-native observability, cost-aware architectural design (FinOps), distributed caching patterns for microservices, and machine learning operationalization for enterprise data platforms. He holds a Master of Science in Computer Science from Lamar University and has published peer-reviewed research on signal processing and simulation techniques.