Shahzad Abdulmajeed

<p>Architected and launched OpenWriterAI, a production-grade, subscription-based AI SaaS platform featuring a decoupled Nest.js backend architecture and a highly reactive Next.js frontend interface.<br>
Built a secure multi-tenant ecosystem featuring LangChain, OpenAI APIs, and a Supabase Vector Database (RAG) to power context-aware features like instant resume generators and text humanization pipelines.<br>
Developed a cross-platform companion browser extension, interfacing with core application APIs via secure WebSockets to deliver native, low-latency, on-page writing assistance to active subscribers.<br>
Integrated robust multi-tenant authentication and Lemon Squeezy webhook gateways, completely automating subscription lifecycle events, recurring billing pipelines, and webhooks processing.<br>
Architected and deployed an enterprise-grade, local-first multimodal AI chatbot platform utilizing Ollama and FastAPI to deliver data-private alternatives to cloud-hosted commercial solutions.<br>
Engineered complex, self-correcting agent execution loops using LangChain and LangGraph, integrating autonomous browser automation to programmatically research and verify live web data.<br>
Developed a high-throughput backend using asynchronous WebSockets to process low-latency, real-time voice streaming and live video chunk analysis, achieving a streaming response threshold under 3 seconds.<br>
Designed a node-based administrative workflow interface in Next.js and Tailwind CSS, enabling real-time multi-model routing, seamless model hot-swapping, and automated failover strategies.<br>
Optimized local hardware resource utilization by implementing model quantization and tensor parallelism strategies, reducing VRAM footprints by 40% while maintaining high token-generation throughput.</p>

<p>Architected and developed FacelessLab, an end-to-end autonomous video generation and publishing platform that automates the entire YouTube content creation lifecycle from a single reference link.<br>
Developed data collection pipelines to scrape YouTube metadata and extract video transcripts, feeding the structured data into fine-tuned GPT models to generate tailored scripts based on user criteria.<br>
Integrated advanced image generation pipelines utilizing Imagen 4 and Nano Banana models to programmatically generate, refine, and execute head-swapping or canvas-drawing for high-conversion video thumbnails.<br>
Engineered asynchronous workflows to stream scripts to the Revid.ai API for video rendering, automatically publishing the finalized media directly to target YouTube via the YouTube Data API.<br>
Implemented robust Redis/Celery background job queues to manage concurrent video rendering tasks, preventing API timeouts and accelerating full-cycle media compilation speeds by 35%.<br>
Architected and deployed an enterprise-grade RAG pipeline that ingested, structured, and indexed a proprietary database of over 100,000+ private newsletter articles for contextual LLM search.<br>
Built an end-to-end automated data ingestion pipeline utilizing n8n, handling HTML extraction, text chunking, and vector database syncing to dynamically update the chatbot as new articles published.<br>
Developed a custom WordPress Single Sign-On (SSO) integration, securing user authentication and providing a seamless interface transition for active portal subscribers.<br>
Engineered the entire application stack using Python (FastAPI/Django) and React/Next.js, optimizing API retrieval loops to ensure low-latency, production-ready response streaming.<br>
Slashed GPT API production costs and token consumption by 40% through the implementation of prompt caching, semantic token pruning, and precise vector meta-filtering to minimize redundant LLM payloads.</p>

<p>Engineered and deployed a production-ready interactive real estate management platform from foundational architecture to live deployment using Next.js and NestJS.<br>
Built an interactive plot mapping and inventory dashboard, enabling administrators to manage property layouts and broadcast real-time availability states across embedded client views.<br>
Implemented a secure multi-tenant infrastructure using Supabase, developing role-based access control (RBAC), user authentication, and scalable TypeScript REST APIs.<br>
Managed the production infrastructure, deployment, and performance monitoring pipelines on Render, optimizing client-side rendering speeds for external third-party site embeds.<br>
Boosted map embed loading speeds by 45% through PostGIS spatial index optimizations and aggressive Redis caching of active plot geometry payloads, drastically cutting server overhead.</p>

<p>Engineered and deployed Attronaut, an enterprise-grade multi-tenant e-commerce analytics platform consolidating real-time storefront revenue and advertising performance data into a unified dashboard.<br>
Configured secure OAuth 2.0 authentication flows and complex webhook gateways to ingest live marketing, spend, and conversion metrics directly from Shopify and Google Ads API environments.<br>
Built high-throughput Django backends paired with asynchronous background workers to execute scheduled data-gathering loops, eliminating manual cross-platform reporting overhead.<br>
Developed a responsive, fluid data-visualization dashboard in Next.js and Tailwind CSS, achieving sub-second interaction latencies and implementing domain-verified email gateways for strict data security.</p>

<p>Deployed scalable Python (Django) and JavaScript enterprise backends, integrating custom machine learning models that boosted application data-forecasting accuracy by 25%.<br>
Architected and optimized real-time computer vision (CNN) data pipelines, streamlining live object detection features to process video streams with zero frame degradation.<br>
Built context-aware NLP modules utilizing advanced text-parsing algorithms, significantly improving automated real-time customer sentiment classification.<br>
Engineered secure Django REST middleware, eliminating common API vulnerabilities and safeguarding multi-tenant data access points against unauthorized execution.<br>
Collaborated with cross-functional product teams in an Agile environment to migrate a monolithic system to an optimized, microservices-driven architecture.</p>