Nithish Suresh Babu
Software Development Engineer - GenAI with expertise in full-stack development and AI integration. Building scalable, multi-tenant platforms and robust data solutions.
Who I Am
I'm a Software Development Engineer - GenAI with expertise in full-stack development and AI integration. I hold a Master's in Computer and Information Science from the University of Michigan (GPA: 3.9) and a Bachelor's from Anna University.
I specialize in building scalable, multi-tenant platforms and designing robust data synchronization systems. My tech stack includes Go, Python, TypeScript, and modern frameworks like Next.js and Vue.js. I'm also experienced in AI/ML.
I'm an active open-source contributor to Google's go-github library, where I've implemented new API methods for GitHub Enterprise. I'm passionate about creating elegant solutions to complex problems and driving innovative, scalable software solutions.
Tech Stack
Project Highlights
Chrono SaaS
AI-powered time tracking with Google Gemini integration
30% productivity increase
Local-Vibes Platform
Real-time event platform with Go backend
Sub-100ms API responses
Tic-Tac-Toe AWS
Multiplayer game on AWS Fargate
100+ concurrent sessions
Production Enterprise App
Kubernetes-orchestrated microservices
99.99% uptime SLA
Recent Projects
Here are some of my recent projects showcasing Go backend development, cloud deployments, and full-stack applications.
Experience
My professional journey and the companies I've had the privilege to work with.
Software Development Engineer - GenAI
CurrentArchitected a multi-tenant centralized backend with Supabase, unifying authentication and user management across multiple company websites, reducing login friction by 30% and enabling scalable access for thousands of users.
Software Developer - Contract
Delivered complete TypeScript schema library and data integration system for 200+ aviation insurance endorsements, automating .docx policy generation with TypeBox validation.
Full Stack Engineer
Developed full-stack applications using Vue.js, Flutter, and Go, serving 100+ researchers with real-time marine data access. Built an offline-first system with automatic sync for preserving data during connection loss.
Research Assistant - GenAI DeepFake
Designed and validated deepfake detection models using TensorFlow, achieving 88.37% accuracy by benchmarking eight models across diverse GenAI image generation datasets. Architected a full-stack Next.js platform for public testing.
Skills & Technologies
Comprehensive tech stack spanning frontend, backend, cloud, and AI. Each skill shows real-world projects where it's applied.
Also experienced with: