Full Stack
Crafting clean, responsive front-ends and robust back-end architectures with real-time capabilities.
DevOps
Deploying scalable applications with containerization, CI/CD pipelines, and infrastructure automation.
Machine Learning
Studying transformer architectures and building production systems with RAG pipelines and agentic workflows.
Who I am
I build end-to-end systems — from clean interfaces to scalable infrastructure.
I found my passion for coding back in college, diving headfirst into full-stack development. Since then I've built a range of end-to-end applications — from real-time collaboration tools to payment systems.
I started with front-end, crafting clean and responsive interfaces. Over time my focus grew into Cloud Infrastructure, DevOps, and AI-driven systems — designing and deploying scalable applications with containerization, CI/CD pipelines, and infrastructure automation.
These days, I'm deep into ML and AI — studying the internals of large language models, from transformer architecture and attention mechanisms to advanced concepts. I've trained and deployed my own models, and built production systems with RAG pipelines, agentic workflows, and tool use.
Away from the keyboard, you'll find me in the world of 2D animation, portrait drawing, and design — bringing characters to life and sketching intricate portraits.
Where I've worked
Packaged App Dev Analyst
June 2026 — PresentAccenture, India
Building and deploying resilient infrastructure automation platforms and ServiceNow workflows across client environments to optimize operations and maintain high availability.
Packaged App Dev Associate
August 2024 — May 2026Accenture, India
Developed and maintained full-stack internal applications and optimized cloud operations utilizing Python, Django and Azure OpenAI.
Where I studied
Ravenshaw University
B.Sc. in Information Technology & Management (87.13%). Built several full-stack projects spanning React.js front-ends, Node.js / MongoDB back-ends, and cloud services like Firebase — laying a solid foundation for my career.
Ravenshaw Higher Secondary School
12th, CHSE Board (94%).
Saraswati Vidya Mandir
10th, BSE Board (91.67%).
Certifications
Tech stack for high performance
Continuous exploration of the best tools to solve complex architectural challenges.
Cloud & DevOps
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Azure
GCP
Docker
Kubernetes
Terraform
Git
AI & Machine Learning
PyTorch
Hugging Face
LangChain'%3e%3cpath%20d='M320,64%20L320,320%20L64,320%20L64,64%20L320,64%20Z%20M171.749388,128%20L146.817842,128%20L99.4840387,256%20L121.976629,256%20L130.913039,230.977%20L187.575039,230.977%20L196.319607,256%20L220.167172,256%20L171.749388,128%20Z%20M260.093778,128%20L237.691519,128%20L237.691519,256%20L260.093778,256%20L260.093778,128%20Z%20M159.094727,149.47526%20L181.409039,213.333%20L137.135039,213.333%20L159.094727,149.47526%20Z%20M341.333333,256%20L384,256%20L384,298.666667%20L341.333333,298.666667%20L341.333333,256%20Z%20M85.3333333,341.333333%20L128,341.333333%20L128,384%20L85.3333333,384%20L85.3333333,341.333333%20Z%20M170.666667,341.333333%20L213.333333,341.333333%20L213.333333,384%20L170.666667,384%20L170.666667,341.333333%20Z%20M85.3333333,0%20L128,0%20L128,42.6666667%20L85.3333333,42.6666667%20L85.3333333,0%20Z%20M256,341.333333%20L298.666667,341.333333%20L298.666667,384%20L256,384%20L256,341.333333%20Z%20M170.666667,0%20L213.333333,0%20L213.333333,42.6666667%20L170.666667,42.6666667%20L170.666667,0%20Z%20M256,0%20L298.666667,0%20L298.666667,42.6666667%20L256,42.6666667%20L256,0%20Z%20M341.333333,170.666667%20L384,170.666667%20L384,213.333333%20L341.333333,213.333333%20L341.333333,170.666667%20Z%20M0,256%20L42.6666667,256%20L42.6666667,298.666667%20L0,298.666667%20L0,256%20Z%20M341.333333,85.3333333%20L384,85.3333333%20L384,128%20L341.333333,128%20L341.333333,85.3333333%20Z%20M0,170.666667%20L42.6666667,170.666667%20L42.6666667,213.333333%20L0,213.333333%20L0,170.666667%20Z%20M0,85.3333333%20L42.6666667,85.3333333%20L42.6666667,128%20L0,128%20L0,85.3333333%20Z'%20id='Combined-Shape'%3e%3c/path%3e%3c/g%3e%3c/g%3e%3c/svg%3e)
Agentic AI
RAGFrontend
ReactJS
TypeScript
JavaScript'%3e%3c/path%3e%3c/g%3e%3c/svg%3e)
Tailwind CSSBackend
ExpressJS'/%3e%3cpath%20d='M128.757%20254.126c64.832%200%2060.784-28.115%2060.784-28.115l-.072-29.127H127.6v-8.745h86.441s41.486%204.705%2041.486-60.712c0-65.416-36.21-63.096-36.21-63.096h-21.61v30.355s1.165%2036.21-35.632%2036.21h-61.362s-34.475-.557-34.475%2033.32v56.013s-5.235%2033.897%2062.518%2033.897zm34.114-19.586a11.12%2011.12%200%200%201-11.13-11.13%2011.12%2011.12%200%200%201%2011.13-11.131%2011.12%2011.12%200%200%201%2011.13%2011.13%2011.12%2011.12%200%200%201-11.13%2011.13z'%20fill='url(%23b)'/%3e%3c/svg%3e)
Python
Django
FastAPI
Redis
Projects
AutoSage: Infrastructure Automation Platform
AutoSage is an AI-driven infrastructure automation platform that streamlines and optimizes cloud operations through workflows, RAG and agentic AI, enabling users to manage and scale their infrastructure efficiently.
SwiftPay: Payment Application
SwiftPay is a demo payment application that allows users to send and receive money instantly, connect with friends, and manage their finances with ease. It is built with a modern tech stack and offers a seamless user experience.
ML Journey & Projects
Building and aligning language models from the ground up — each version pushing further than the last.
MiniGPT-Shakespeare
Where it started — a GPT-style transformer trained entirely from scratch in PyTorch on the works of Shakespeare, then deployed on HuggingFace Spaces with a Gradio interface for interactive text generation.
MiniGPT-v2
A GPT-style transformer built from scratch in PyTorch and trained on the TinyStories dataset. It layers in modern techniques — RMSNorm, SwiGLU, RoPE, GQA, LR scheduling and a hand-rolled BPE tokenizer — to improve quality and efficiency in text generation.
MiniGPT-v3
A fine-tuned SmolLM-135M taken through a complete alignment pipeline — Continued Pre-Training (CPT) on WikiText, Supervised Fine-Tuning (SFT) on Alpaca, preference alignment via RLHF/DPO on Orca pairs, and RLVR with GRPO for verifiable arithmetic reasoning. Each stage is a stackable LoRA adapter, served on Streamlit.
Let's build something extraordinary.
Have a project in mind, a role to fill, or just want to say hi? My inbox is always open — I'll try to get back to you within 24 hours.