AI Developer & Engineer @ MGC | Aspiring AI Orchestration | Python, LangGraph, RAG, n8n
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Arryan Rabbani는 Zinn Hub에 자신의 기술을 입증하고 작업 증거를 제공했습니다. 모든 검증된 Zinner는 실습 품질 보증 검토를 통과하므로 안심하고 고용할 수 있습니다.
🛡️ September 2026부터 인증됨
I am an AI Developer and Engineer currently working at MGC Developments, where I contribute to building real-world AI automation platforms. My core focus is on AI Orchestration, Multi-Agent Systems, and Full Stack Development. I specialize in building scalable, production-ready AI workflows using Python, LangGraph, LangChain, FastAPI, and React.
At MGC, I have worked on innovative projects like MGC AutoPost, an AI-powered social media automation tool. This experience has given me hands-on exposure to integrating AI models, handling backend systems, and automating multi-platform workflows.
Beyond traditional development, I have strong expertise in workflow automation using n8n. I help businesses connect their daily tools (like Google Sheets, CRMs, and Slack) and eliminate repetitive manual tasks. Whether it's an AI-powered email responder or a complex data syncing pipeline, I can build it. I also have experience in AI-powered web scraping, extracting data from dynamic websites and feeding it directly into databases.
I am also skilled in building custom RAG (Retrieval-Augmented Generation) chatbots that allow users to chat with their own documents and databases. By combining LangChain, vector databases, and FastAPI, I create intelligent backends that power modern web applications.
I believe in clear communication, clean code, and timely delivery. I am passionate about staying at the forefront of AI technology and am always eager to take on new challenges. If you are looking for a reliable freelancer to build your next AI project, automate your workflows with n8n, or develop a full-stack application, let's connect and bring your vision to life. I am committed to delivering high-quality results that help your business grow.
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Built a multi-agent LangGraph-style workflow (Recon → Scanner → Exploit → Report) with a Roman Urdu AI console, CVSS risk scoring, and PDF report generation.
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Built a multi-agent LangGraph-style workflow (Recon → Scanner → Exploit → Report) with a Roman Urdu AI console, CVSS risk scoring, and PDF report generation.
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