Wajih Ul Hassan

About Me

I’m a Full Stack & AI Engineer with 5+ years of experience shipping end-to-end products — from React and Next.js interfaces to FastAPI and Django backends, plus the LLM and computer-vision systems that power them. I build fast, accessible UIs with TypeScript and Tailwind CSS, and pair them with robust APIs, PostgreSQL data layers, and async job pipelines.

What I enjoy most is owning the full product surface — API design, database schema, frontend UX, and AI integration in one cohesive stack. Whether it’s a RAG-powered chat app, an ATS with event-driven AI scoring, or a serverless OCR pipeline on AWS Lambda, I focus on shipping complete features that work in production.

Focus Areas

Full Stack — React, Next.js, TypeScript, Tailwind CSS, FastAPI, Django/DRF, GraphQL, PostgreSQL, Redis, and React Native.

AI / ML — LangChain, RAG pipelines, OpenAI/AWS Bedrock integrations, YOLOv11 computer vision, and serverless AI workflows on AWS Lambda.

Key Projects at Conovo

SharpBrains — AI-powered Applicant Tracking System built on Django 6 / DRF. Features automated resume scoring, candidate pipelines, interview scheduling, and offer management. Designed with an event-driven architecture (Celery + Redis + transactional event log) that decouples AI scoring from core domain logic. Integrated with OpenAI, Zoom, and Veriff.

Epiphany — Mental-health RAG chatbot built with FastAPI, LangChain, and FAISS over a curated knowledge base. Serves LLM responses via AWS Bedrock with PostgreSQL persistence.

Scanning Automation — Computer-vision OCR pipeline using YOLOv11 for document region detection, ResNet18 for orientation correction, Google Vision for OCR, and LLMs for structured data extraction. Elasticsearch-indexed for fast record search.

TextBehind Serverless AI Pipeline — Fully serverless content pipeline on AWS Lambda orchestrated by Step Functions: OCR (Textract) → image captioning (Bedrock Pixtral) → summarization → tone detection → content matching. Includes real-time multi-language translation via AWS Translate over WebSockets.