m
mfaizanar

Faizan Arshad

@mfaizanar
5,0(2)

I Build AI Agents, RAG Pipelines, and Full Stack Apps That Work in Production

Pakistan
Anglais
Certaines informations sont présentées en anglais.
À propos de moi
I am a full stack developer and AI engineer with four plus years shipping software to production, not just demos. Expertise covers LLM integration, AI agents, and RAG systems using LangChain, LangGraph, and Claude and OpenAI APIs, backed by React, Next.js, Node.js, and PostgreSQL. My services include RAG chatbots on your own data, AI agents that call tools and take real actions, full stack apps with AI built in, and computer vision or data extraction pipelines. I am available 24/7 and happy to set up a quick Zoom call early on so we can walk through your requirements and start drafting.... Plus d’infos

Compétences

m
mfaizanar
Faizan Arshad
hors ligne • 

Voir mes services

Cours de codage en ligne
I will teach python programming and data science
5,0(1)
Développement de chatbots d'IA
I will build production ready ai agents, rag systems, and llm saas apps

Portfolio

Expérience professionnelle

Full Stack Developer & AI Engineer (AI Agents, RAG, LLM)

NASTP • Temps plein

Feb 2022 - Present • 4 yrs 8 mos

-Designed, prototyped, and deployed production LLM agents and RAG pipelines using LangChain and LangGraph for clients across healthcare, finance, and technology. -Built an agentic clinic scheduling assistant using the Claude API with real tool calling for live schedule reads and updates, applying ReAct style reasoning to decide when to query data, ask a clarifying question, or confirm an action. -Designed scalable RAG document retrieval pipelines over private knowledge bases for enterprise clients, including a legal research system over 10,000 plus documents that cut research time by 70 percent. -Conducted structured AI evaluation and benchmarking sessions for a client's AI product, assessing model behavior, reliability, and output quality across candidate LLMs. -Built and deployed full stack applications with Node.js, React.js, and FastAPI, containerized with Docker and deployed to AWS and GCP. -Designed and deployed machine learning and deep learning models in Python, TensorFlow, and PyTorch for applied problems in healthcare and finance, packaging solutions with MLflow and Docker for production use. -Built interactive dashboards in Streamlit, Gradio, and Tableau that made model outputs interpretable for non technical stakeholders.

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  • À recommander à un ami
    5
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    5
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