Sanath Rao Uppoor
Graduate Software Engineer with 4+ years of backend systems engineering experience (Golang, Java, Python), now pursuing MSc Applied AI at Warwick. Strong foundations in C/C++, computer architecture, Linux, embedded concepts, concurrency, and performance optimisation. Open to backend, platform, and applied AI roles.
Worked with
Experience
4+ years building backend platforms, SRE tooling, and scalable systems in fintech, healthcare, and applied AI.
Engineer II - American Express
Optimised Golang microservices processing 12K-18K requests/min, reducing API latency by 30%. Improved reliability to 99.9% uptime with profiling, heap snapshots, and p99 tuning. Built secure REST integrations and observability that cut RCA time by 40%.
Software Engineer - TCS
Engineered high-availability microservices managing 4.4M+ medical devices with 99.9% uptime. Built ingestion pipelines reducing device creation time by 90% with efficient JSON validation, parsing, and caching. Improved traceability and compliance across 3 continents.
ML Intern - RV CISCO CoE
Built a TensorFlow pipeline for augmented respiratory health monitoring, improving diagnostic accuracy by 18% and achieving >90% precision. Implemented augmentation, contrast enhancement, and model fine-tuning across 3 disease classes.
Skills
Tools, platforms, and technologies I use for backend systems, cloud, and AI/ML.
Education
Academic background and certifications focused on applied AI, systems engineering, and cloud development.
MSc in Applied Artificial Intelligence (Sep 2025 - Sep 2026). WMG Excellence Scholarship recipient (GBP 10,000).
University of Warwick
Visveswaraya Technological University, B.E. in Electronics and Communication (Aug 2017 - Aug 2021), GPA 8.22/10.
VTU - B.E. ECE
Certifications
Projects
Selected projects in observability, AI/ML, and applied systems engineering.
AI SRE for Root Cause Identification
Built a Golang-based log-fingerprinting engine processing 5K+ logs/min, identifying anomalies and reducing RCA time by 40% through high-performance batching and concurrent parsing.
Deep Learning Precision Farming
Created and cleaned a dataset of 6,000+ leaf images and built a transfer-learning CNN achieving 94.8% accuracy across 5 disease classes.
Get In Touch
Coventry, United Kingdom | sanathrao.1999@gmail.com | +44 7833 055630