About Me
I am an AI Systems Engineer and 4th-year Computer Science student at IIIT Vadodara (Class of 2027), specializing in Agentic AI, LLM applications, and scalable backend architecture. My experience spans production FastAPI & Django microservices, multi-agent workflows with LangGraph, advanced RAG architectures, and Clinical NLP research (PubMedBERT & Federated Learning). I design production-oriented AI infrastructure that connects reliable APIs, retrieval systems, and transformer-based workflows.
Talk to My AI Digital Twin
Instead of browsing a static resume, chat directly with my AI agent. Trained on all my systems architectures, hackathon wins (Google Build with AI), Clinical NLP research, and live code repositories.
Skills & Technologies
AI & Agentic Systems
Machine Learning & NLP
Backend Engineering
Databases & Cloud DevOps
Professional Experience
AI Backend Engineer Intern
Quba Infotech • Gandhinagar, Gujarat
- Architected modular FastAPI & Django services and REST APIs, separating transcript, retrieval, and generation concerns.
- Orchestrated provider-agnostic OpenAI and Ollama integrations, enabling model switching without vendor coupling.
- Established Pydantic request and response contracts to validate structured AI outputs across modular services.
- Designed QdrantDB retrieval interfaces that isolated vector search and contextual memory from application logic.
Research Intern (Clinical NLP & Federated Learning)
Indian Institute of Information Technology Vadodara • Mentor: Dr. Sanjay Saxena
- Architected a centralized Clinical NLP pipeline for ICD prediction across approximately 298,000 MIMIC-IV clinical records (validated on an initial subset of 5,000 discharge summaries).
- Engineered PubMedBERT preprocessing with dataset integration, ICD mapping, and hierarchical multi-label classification targets.
- Optimized long-document training with sliding-window tokenization, class-balanced focal loss, AMP, and checkpointing.
- Established threshold optimization and a centralized baseline for privacy-preserving Federated Learning integration.
Backend Engineer Intern
Glynac AI • US-based, Remote
- Engineered Django and Python REST APIs supporting reusable backend integrations for AI SaaS workflows.
- Integrated multi-system data pipelines to standardize data exchange across internal services.
- Optimized backend efficiency by 15% by resolving N+1 queries and adding targeted database indexes on critical endpoints.
Featured Projects
CleaniSense
Google Hackathon WinnerAI-powered civic platform for environmental monitoring and citizen grievance reporting. Led the engineering team in delivering an AI image validation pipeline for complaint verification, automated municipal department routing, and live tracking dashboards. Won 2nd Runner-Up nationally at Google's "Build with AI: Code for Communities".
AI Meeting Assistant
Unified platform for transcript intelligence, semantic search, and automated note generation. Reduced redundant transcript processing by 70–78% with semantic clustering and hierarchical summarization, lowering LLM inference costs. Engineered QdrantDB-backed RAG for semantic search and transcript-grounded contextual analysis.
LeapSQL-AI
Enterprise-grade Natural Language to SQL platform. Architected a secure 3-agent LangGraph pipeline (generator, evaluator, executor) with a 5-layer security model to prevent any destructive or malformed queries from reaching the database.
Trading Alert System
Real-time event-driven alert engine computing 5 technical indicators (RSI, MACD, Bollinger Bands, SMA, ATR) via Angel One SmartAPI. Built an asynchronous alert engine using Celery + Redis evaluating multi-condition logic across 100+ tickers concurrently.
Honors & Achievements
2nd Runner-Up — Google Build with AI
Won 2nd Runner-Up in the "Clean Air & Clear Streets" category at Google's national Build with AI: Code for Communities hackathon. Led the engineering team and presented CleaniSense at the National Showcase in New Delhi before 11+ Members of Parliament.
Clinical NLP & Federated Learning
Selected for Research Internship at IIIT Vadodara under Dr. Sanjay Saxena working on MIMIC-IV Clinical NLP & Federated Learning. Research abstract selected for IEEE Transactions on Computational Imaging.
Education & Certifications
B.Tech in Computer Science & Engineering
Indian Institute of Information Technology, Vadodara
Certifications
- Postman API Student Expert 2025
- Fundamentals of Deep Learning (NVIDIA DLI) 2025
- Django Certification (Simplilearn) 2025
- Microsoft Learn Student Ambassador 2024
Leadership & Extracurriculars
Social Media Lead
Arcadia - Gaming Club of IIIT Vadodara
May 2024 - April 2025Member
Technical Committee IIITV
Jan 2025 - April 2025Member
IIITV Finance & Consulting Club
Aug 2023 - Sept 2024Ready to Connect?
I'm always open to discussing backend engineering roles, AI systems, or exciting open-source collaborations. Drop me a message!