Junaid Ali Bhatti

Hi, my name is 

Junaid Ali Bhatti 

I am a Senior AI Engineer with 4 years of experience building production LLM agent systems and the platforms that run them: LangGraph and LangChain workflows, MCP integrations, RAG over vector databases and multi-tenant FastAPI and Next.js apps deployed on AWS. My MS thesis introduced a novel GAN architecture that outperforms 14 published baselines, so I build models as well as integrate them.

0+Years of experience
0%RAG retrieval accuracy
0+AI products built
0+Engineers led

Skills 

NextJS

NextJS

React JS

React JS

Typescript

Typescript

Javascript

Javascript

Python

Python

FastAPI

FastAPI

Django

Django

Node JS

Node JS

LangGraph

LangGraph

Pinecone

Pinecone

TensorFlow

TensorFlow

Pandas

Pandas

Numpy

Numpy

PostgreSQL

PostgreSQL

Mongo DB

Mongo DB

SQL

SQL

GEE

GEE

Sentinel Hub

Sentinel Hub

Tailwind

Tailwind

GitHub

GitHub

MCP

MCP

Claude API

Claude API

OpenAI API

Gemini API

Gemini API

AWS

AWS

Docker

Docker

Redis

Redis

PyTorch

PyTorch

Scikit-learn

Scikit-learn

OpenCV

Linux

Linux

Experience 

Senior AI Engineer@Techesthete

Oct 2026 - Present

  • Build and deploy AI agents and agentic workflows with LangChain and LangGraph, integrating OpenAI, Claude and Gemini models.
  • Develop LLM-powered applications and RAG workflows over vector databases, from ingestion to grounded responses.
  • Build MCP integrations that give LLM agents controlled access to tools and data.
  • Develop Python and Node.js backend services and React.js AI interfaces, and deploy them to production.

Education 

  1. Master of Science In Computer Science

    COMSATS University Islamabad(CUI), Lahore Campus

    Thesis: GAN-based spatio-temporal fusion of drone and satellite imagery for precision agriculture. Relevant courses included Advanced Computer Vision, Pattern Recognition, Machine Learning and AI.

  2. Bachelor of Science In Computer Science

    COMSATS University Islamabad(CUI), Lahore Campus

    Relevant Courses included Data Structures and Algorithms, Computer Vision and Artificial Intelligence.

My Work 

Some of my production work is under NDA. I'm happy to walk through the architecture and my contribution in an interview.

CropSight
AgriTech PlatformLive

CropSight

End-to-end farm and agri-project platform serving individual farms through to sugar and wheat mills, with web and Play Store mobile apps. GPS boundary mapping, crop-health classification via Google Earth Engine, geo-tagged task verification, weather alerts, yield forecasting and stakeholder dashboards.

Next.js
Django
PostgreSQL
Sentinel Hub
Google Earth Engine
Leaflet
Mapbox
AI PlatformLive

PropAI

WhatsApp-first multi-tenant SaaS where real estate agents run their entire lead, buyer and listing pipeline through chat. Claude drives lead qualification and daily agent briefings, and pgvector matches buyers to listings semantically. Includes tenant-scoped RBAC, 2FA, Playwright listing ingestion and Stripe usage metering.

FastAPI
PostgreSQL
pgvector
Redis/ARQ
Claude API
Next.js
Stripe
AWS
AI PlatformLive

Marginalia

Chat-with-your-PDF study platform. Answers carry page citations that open the PDF at the exact page, and each document also generates summaries, flashcards and quizzes. A durable Inngest pipeline handles parsing, chunking, embedding and generation with retries. The AI layer is provider-agnostic (OpenAI or Gemini) with bring-your-own-key and AES-256-GCM encrypted keys.

Next.js
TypeScript
pgvector
Prisma
Inngest
Vercel AI SDK
AI Health Companion

Symptoms Sense

Conversational health assistant: describe symptoms, get pointed to the right specialist with urgency flags (information only, never a diagnosis), then book an appointment or set a medicine reminder in one chat. A tool-calling agent uses a propose-then-confirm design, so nothing is written until the user confirms.

FastAPI
OpenAI function calling
PostgreSQL
Next.js
TypeScript
Docker
GAN-Based Drone & Satellite Fusion
MS Thesis

GAN-Based Drone & Satellite Fusion

GAN framework fusing drone imagery with 10 m Sentinel-2 data, using a spectral attention encoder and a multi-task segmentation head for weed, lodging and boundary detection. Reaches 32.94 dB PSNR on a self-collected set of 11,325 annotated patch pairs, and runs CPU-only after INT8 quantisation (230 MB, down from 850 MB).

PyTorch
GANs
Attention
Multi-Task Learning
Quantization
Sentinel-2

Other Work

Kidney Stone Detection

CT image analysis comparing a CNN with an SVM + HOG baseline, served through Gradio.

Python · CNN · SVM · Gradio

TEDx COMSATS

Official website for TEDxCOMSATS Lahore 2024, built as part of the Web & IT team.

Next.js · TypeScript · Framer Motion · Tailwind

NFT Arena

NFT marketplace on Ethereum where creators mint and collectors trade digital art.

Next.js · TypeScript · Ethereum · IPFS

Media Server

Media server for streaming and managing digital content. Minimal HTTP API to upload media to disk and serve it

Express · Javascript