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faizhassan11

Faizdevloper

@faizhassan11

Ignite Your Brand With AI Solutions and Custom Website

Pakistan
Engels, Urdu, Frans, Spaans
Sommige informatie wordt in het Engels weergegeven.
Over mij
I’m a Full-Stack AI Developer with hands-on experience building AI-powered web applications, chatbots, automation tools, and intelligent systems that solve real business problems. I specialize in end-to-end AI solutions — from idea to deployment. 🚀 What I Do Best ✅ AI & LLM-based Applications (ChatGPT, LLaMA, Gemini, Groq) ✅ Full-Stack Web Development (Frontend + Backend) ✅ AI Chatbots & Virtual Assistants ✅ RAG Systems (Vector Databases, Embeddings, Retrieval) ✅ Automation & AI Agents ✅ API Development & Integration ✅ Streamlit, Flask, FastAPI Applications ✅ Database & Cloud-Ready Solution... Lees meer

Skills

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faizhassan11
Faizdevloper
offline • 
Gemiddelde reactietijd: 3 uur

Bekijk mijn diensten

AI-integraties
I will build ai chatbots and ai agents for your business
VanafUS$ 100 / projectMeer informatie
AI websites & software
I will develop a custom ai chatbot using chatgpt, openai, and gpt4
VanafUS$ 125 / projectMeer informatie

Portfolio

Werkervaring

SYSTEMIQ

Full Stack AI Engineer

SYSTEMIQ • Fulltime

Nov 2020 - Present • 5 yrs 8 mos

Architected and deployed production-ready, multi-agent conversational platforms using LangChain and LangGraph, wrapping advanced AI logic into scalable FastAPI backend services. Engineered end-to-end RAG pipelines connecting high-performance vector databases with unstructured knowledge bases, designing efficient data schemas and streaming ingestion workflows. Developed full-stack streaming interfaces using modern web technologies, incorporating Server-Sent Events (SSE) and WebSockets to deliver real-time, token-level UI rendering for seamless user experiences. Optimized system latency and response accuracy by tuning embedding models, implementing advanced prompt engineering frameworks, and structuring deterministic JSON outputs for reliable frontend state management. Managed cloud-native deployments on AWS by containerizing services with Docker, setting up robust API gateways, and implementing observability patterns to monitor system health and LLM token usage.