B.Tech CSE @PSIT Kanpur | π National Finalist @IndiaInnovates2026 | Engineering Full-Stack Systems with React Β· Node.js Β· MongoDB | Building Agentic AI Β· RAG Pipelines Β· LangChain workflows | 7 Live Deployed Projects spanning E-Commerce, Civic-Tech, Multi-Tenant SaaS & AI Ops | 200+ LeetCode Problems | HackerRank 4β Java | AWS Summit Champion | Simulations @JP Morgan & @Deloitte | Hardcore DSA Practitioner β€οΈ | Open Source Contributor
ποΈ Full-Stack Engineer & AI/ML Builder β B.Tech Computer Science, PSIT Kanpur
π Shipping full-stack products end-to-end β 7 of my projects are live and deployed, not just repos
π§ Layering LLM intelligence on top of traditional stacks β RAG pipelines, semantic search, LangChain workflows, prompt engineering
π National Finalist, India Innovates 2026 β for CivicSentinel, an AI civic-tech platform
π Comfortable across the full stack: auth systems, payment infra (Stripe), multi-tenant architecture, database design, deployment
πΌ Completed structured engineering simulations at JP Morgan (Software Engineering) and Deloitte (Technology Consulting)
β€οΈ Hardcore DSA practitioner β 200+ problems solved on LeetCode, HackerRank 4β in Java
βοΈ AWS Summit Champion β AWS Summit India Online 2026
π MERN Full-Stack Certified β Tryst, IIT Delhi
π Open to Software Engineering Internships, AI/ML roles, and open source collaboration
philosophy: "Ship fast, engineer for scale, design with intent"
currently:
building: "Production-grade AI-powered SaaS applications"
learning: "Advanced System Design & Distributed Architectures"
exploring: "Vector Databases, Agentic AI, Multi-Agent Workflows"| Degree | B.Tech, Computer Science & Engineering |
| Institute | PSIT Kanpur |
| GPA | 7.27 |
| Location | Kanpur, Uttar Pradesh, India |
| Domain | Level | Where I've Applied It |
|---|---|---|
| Prompt Engineering | π©π©π©π©π© | Structured prompting across every AI project I've shipped |
| LLM Integration | π©π©π©π©β¬ | OpenAI & Gemini APIs β production prompt orchestration (CivicSentinel) |
| RAG Pipelines | π©π©π©π©β¬ | Real-time contextual retrieval over civic-complaint knowledge bases |
| LangChain | π©π©π©π©β¬ | Chained workflows for semantic classification & retrieval |
| Semantic Search | π©π©π©π©β¬ | Context-aware query retrieval over custom knowledge bases |
| Repository | Description |
|---|---|
| ποΈ society-maintenance-tracker | Multi-tenant complaint & notice-board platform for apartment societies |
| π± sprout-task-tracker | MERN Kanban task tracker where tasks visually grow as they progress |
| πΌ Portfolio | Personal portfolio site showcasing projects, skills, and experience |
| π Aditya-dxt | This profile README |
π Live: sneakervault-india.vercel.app Β· Repo: View Source
- Architected an enterprise-style e-commerce platform covering the full order lifecycle β cart, checkout, payment, fulfillment, and admin management β built with React, Node.js, Express, MongoDB, and Next.js, deployed end-to-end on Vercel (frontend) and Render (backend).
- Implemented a secure authentication layer using JWT with Role-Based Access Control (RBAC), cleanly separating user and admin permissions across every protected route.
- Integrated Stripe for end-to-end payment processing, handling checkout, order confirmation, and payment-state syncing across the order pipeline.
- Optimized MongoDB query patterns and indexing strategy, reducing API latency by ~35% under real usage load.
- Diagnosed and resolved a production CORS incident post-deployment across the Vercel/Render split-origin setup, restoring full frontendβbackend connectivity with zero downtime.
π Repo: View Source Β· π National Finalist β India Innovates 2026
- Built an AI-powered civic-tech platform that ingests citizen complaints in real time, tagging each with geolocation data for downstream routing and analysis.
- Designed a semantic classification pipeline using the OpenAI API and LangChain, automatically categorizing incoming complaints by type, urgency, and department relevance.
- Implemented a RAG-based retrieval layer to surface contextually similar past complaints and precedent resolutions, helping civic authorities act on actionable insights faster.
- Shipped separate Citizen and Admin dashboards β citizens track complaint status end-to-end, while admins get an aggregated, filterable operations view.
- Recognized as a National Finalist at India Innovates 2026 for real-world civic innovation impact.
π Live: railsage-ai.vercel.app Β· Repo: View Source
- Built an AI-powered railway operations command center for the FAR AWAY Hackathon 2026, collaboratively with @indeedvaibhav, using React 19, Vite, Node.js, Express, Leaflet, and GSAP.
- Integrated the Anthropic Claude API to power a multi-step reasoning feed, giving operators full transparency into each AI-driven decision as it happens rather than a black-box output.
- Implemented live map-based tracking with Leaflet, visualizing train positions and route data in real time for operational decision-making.
- Added multilingual announcement support across English, Hindi, and Japanese, making the system usable across diverse operator and passenger bases.
- Designed smooth, motion-driven UI transitions with GSAP to keep a data-dense operations dashboard feeling responsive rather than cluttered.
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JP Morgan Β· 2026 Software Engineering Job Simulation
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Deloitte Β· 2026 Technology Job Simulation
|
| Recognition | Details |
|---|---|
| π₯ National Finalist | India Innovates 2026 β National-level innovation competition |
| π Rank 1 β IEEE Summer of Code 2026 | Final Selection round, IEEE Student Branch, Graphic Era Hill University |
| π State-Level Athlete | Basketball, representing Kanpur Nagar |
| βοΈ AWS Summit Champion | AWS Summit India Online 2026 |
| π MERN Full-Stack Certified | Tryst, IIT Delhi |
| π€ E-Summit IIT Kanpur | 2K24 & 2K25 editions |
| π§© Bitathon & TATA Crucible | Hackathon & quiz participation, 2025 |
| π€ AI Bootcamp Graduate | 3-Day AI/ML workshop |
| πΌ JP Morgan & Deloitte | Software Engineering & Technology simulations |
| Area | Focus |
|---|---|
| π Learning | Advanced System Design & Distributed Architectures Β· Deep Learning Fundamentals |
| ποΈ Building | Production-grade AI-powered SaaS applications Β· Scalable full-stack systems |
| π Exploring | Vector Databases Β· Advanced RAG Architectures Β· Agentic AI & Multi-Agent Workflows |
| π― Open To | Software Engineering Internships Β· AI/ML Collaborations Β· Open Source Contributions |

