Backend-focused developer building scalable systems with Flask, Django, and AI-powered pipelines (RAG, NLP).
I design and ship backend-first platforms with clean APIs, resilient architecture, and measurable performance. My recent work focuses on RAG pipelines, semantic retrieval, and production-oriented AI services that solve real user workflows.
Architecture Focus
Production-oriented backend architectures built for reliability, performance, and clean delivery. This section describes how I design software, while the stack below shows the tools I use.
Service boundaries, request validation, auth, and response shaping for maintainable backend contracts.
Vector search, reranking, grounding, and prompt flow design for document-heavy AI products.
Background tasks, state changes, and workflow automation for real-time product behavior.
Low-latency event handling, streaming updates, and alert loops for time-sensitive use cases.
Deployment-friendly systems with logging, stability checks, and production readiness in mind.
Python, JavaScript, C, SQL, HTML/CSS
Tool Stack
Languages, frameworks, and tooling I use to build and ship the systems above.
Flask, Django, ReactJS, Postman, Figma, Power BI
TensorFlow, RNN, Transformers, RAG, NLP, Computer Vision
Docker, Git, AWS (Basic), Linux Terminal, CI/CD
Implemented RNN, Transformers, and RAG models in TensorFlow to build a chatbot trained on web-scraped data. Gained experience in building production-ready AI systems.
Majoring in Artificial Intelligence and Data Science with a strong focus on machine learning, deep learning, and data analysis.
Science stream with Physics, Chemistry, and Mathematics specialization.
Exceptional academic performance in CBSE Board Examination.
Built a scalable Flask backend with RAG retrieval over legal corpora, enabling low-latency legal guidance with grounded responses.
System: RAG Pipeline | Vector DB | API Backend | Auth
Key Features:
Designed an API-first resume optimization service with NLP scoring, structured parsing, and export-ready ATS document generation.
System: API Backend | NLP Scorer | Template Engine | Export Service
Key Features:
Loan decision dashboard that helps lenders evaluate applicant risk and approve applications with explainable ML insights.
System: ML Scoring API | Analytics Dashboard | Feature Pipeline
Key Features:
Built a Django-based rental backend with inventory workflows, booking state transitions, and role-based operations for admin and users.
System: API Backend | SQL Data Model | Booking Engine | Auth
Key Features:
Personalized movie recommendation engine combining text similarity and collaborative signals for accurate discovery.
System: Retrieval Engine | Ranking Pipeline | Recommendation API
Key Features:
Engineered a real-time CV backend pipeline for drowsiness detection with event-driven alerting and low-latency inference.
System: CV Inference Pipeline | Event Stream | Alert Engine
Key Features:
Classic Python arcade bundle combining multiple mini-games under one launcher with smooth keyboard-first controls.
System: Modular Game Engine | UI Launcher | Input Loop
Key Features:
Interactive number-theory visualizer that maps Collatz sequences into clear, explorable graph patterns.
System: Computation Pipeline | Visualization Layer | Interactive Controls
Key Features:
Academic performance companion for Mumbai University students to compute CGPA, trends, and target planning instantly.
System: Client-side Calculator Engine | Rules Mapper | Report Generator
Key Features:
Image-to-meme generator that transforms user photos into share-ready meme cards using multimodal AI captioning.
System: Multimodal Inference API | Caption Pipeline | Media Renderer
Key Features:
I'm always interested in hearing about new projects and opportunities. Feel free to reach out using any of the methods below.