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Achievement: YOLOAchievement: Pair ExtraordinaireAchievement: Pull Sharkx2

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mydafzal/README.md

Maida Afzal

AI Engineer · Full-Stack Software Engineer · Automation Builder

I build AI-powered products, agentic workflows, SaaS platforms, RAG systems, and production-ready backend services.

About

I am a software engineer focused on practical AI systems: applications that connect language models, data pipelines, business logic, and real user workflows.

My work sits at the intersection of AI engineering and full-stack product development. I enjoy building systems that move beyond demos: authenticated SaaS apps, AI support agents, vector-search backends, ML prediction pipelines, automation platforms, and integrations with third-party APIs.

What I Build

  • AI agents and multi-step automation workflows
  • RAG and vector-search applications using OpenAI, LangChain, ChromaDB, FAISS, and Qdrant
  • Full-stack SaaS products with Next.js, TypeScript, Prisma, auth, billing, and dashboards
  • Backend services with FastAPI, Express, NestJS, PostgreSQL, Redis, and background jobs
  • ML/data pipelines for prediction, scoring, and analytics
  • API integrations with Stripe, Twilio, Google APIs, HubSpot, WooCommerce, cloud storage, and CRM systems

Technical Toolkit

TypeScript Python Node.js React Next.js React Native FastAPI Express NestJS OpenAI LangChain TensorFlow PyTorch Scikit-Learn Pandas NumPy PostgreSQL Redis MongoDB Prisma Docker AWS Google Cloud Platform GitHub Actions

AI and ML: OpenAI, LangChain, LangGraph, CrewAI, FAISS, ChromaDB, Qdrant, Gemini, XGBoost, scikit-learn, pandas, NumPy

Backend: FastAPI, Express.js, NestJS, Node.js, Python, TypeScript, PostgreSQL, Redis, Sequelize, Prisma, SQLModel

Frontend: Next.js, React, React Native, Tailwind CSS, Radix UI, Vite

Cloud and Integrations: Docker, AWS S3, Azure Blob Storage, Stripe, Twilio, Google APIs, HubSpot, WooCommerce, SendGrid

Product Engineering: auth, subscriptions, dashboards, background jobs, API design, webhooks, admin tooling, testing, documentation

Current Focus

  • Building agentic systems that can use tools, retrieve context, and complete business workflows
  • Designing backend architectures for AI products that need memory, permissions, billing, and integrations
  • Turning complex product ideas into usable software with clean APIs and practical UX

Pinned Loading

  1. ai-marketing-studio ai-marketing-studio Public

    Full-stack AI marketing automation workspace for campaign creation, creative generation, and ad performance analysis.

    TypeScript 1

  2. ai-support-platform-backend ai-support-platform-backend Public

    Multi-tenant AI support platform backend with LangChain, LangGraph, ChromaDB, PostgreSQL, Redis, and business integrations.

    JavaScript

  3. product-lifecycle-agent product-lifecycle-agent Public

    AI-assisted multi-agent workflow for SKU analysis, pricing, marketing, finance, governance, and lifecycle reporting.

    Python 1

  4. ecommerce-chatbot-backend ecommerce-chatbot-backend Public

    TypeScript backend for a WooCommerce-aware AI shopping assistant using LangChain, OpenAI, ChromaDB, and Redis.

    TypeScript

  5. wise-sports-predictor wise-sports-predictor Public

    Machine-learning pipeline and FastAPI service for NBA and MLB predictions with XGBoost and data-processing workflows.

    Python

  6. contractbot-saas contractbot-saas Public

    Full-stack contract workflow SaaS with Next.js, Prisma, NextAuth, tRPC, Stripe, SendGrid, and Playwright tests.

    TypeScript