
RAJITH S
Software Developer, Cloud Native & DevOps Engineer
Designing modern software systems that integrate high-quality engineering practices, Cloud and DevOps workflows, advanced networking, and AI-enhanced intelligence. Dedicated to creating scalable, resilient, and efficient solutions tailored for real-world impact.
About Me
Executive Profile
Hi, I’m Rajith S.
You don’t know me yet — but I build systems that do more than just run.
I don’t just write code. I build systems that think, scale, and survive production.
From AI-driven intelligence to cloud-native architectures, I turn raw ideas into systems that actually work — not just in theory, but under real-world pressure.
I operate at the intersection of:
· Software Engineering
· Cloud & DevOps
· Networking
· Artificial Intelligence
I’m driven by one thing:
taking complex systems from prototype → production — without breaking them.
Tech Arsenal
Featured Projects
ChargeIQ
Real-time EV charging discovery system with geolocation, live availability, and optimized navigation routing.
Smart Employee Onboarding Identity Service
Serverless onboarding workflow orchestrating identity verification, document pipelines, and secure stage-based access.
Smart Toll System
Automated toll collection system leveraging real-time vehicle detection and seamless transaction processing.
ECG Arrhythmia Classification
Deep learning pipeline for ECG signal preprocessing, feature extraction, and arrhythmia classification with explainability.
Professional Experience
AWS Cloud Intern
ActiveF13 Technologies
Migrating on-premise applications to AWS cloud platform.
Software Engineering Intern
YugaYatra Retail (OPC) Pvt. Ltd.
Developing web applications for YugaYatra Retail (OPC) Pvt. Ltd. using React, Node.js, and MongoDB.
President
Intel IoT Club
Led cross-domain build sprints, managed partnerships, and scaled the club’s research pods focused on AI for IoT.
Co-Lead
Intel IoT Club
Designed learning roadmaps, introduced rapid prototyping practices, and mentored cohorts on embedded + cloud stacks.
Research & Publications
Deep Learning Architectures for Skin Lesion Classification
A Comparative Study of CNN, Transformer and Hybrid Models
IEEE ICISCoIS 2026