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mmwady/README.md

Hi, I'm Mohamed Wady 👋

Senior AI Engineer · Agentic Systems & RAG · 14+ years bridging mission-critical telecom and modern software

🌐 Portfolio · 💼 LinkedIn · 📧 mmwady@gmail.com · 📍 Cairo, Egypt

🟢 Open to remote Senior AI Engineering roles — Agentic Workflows · RAG · LLM Integration · Flutter


👋 About

I build production-grade AI agents and RAG systems for domains where correctness, traceability, and constraints actually matter — telecom operations, satellite networks, and regulated environments.

For 14+ years I've worked at the intersection of mission-critical infrastructure (satellite/VSAT networks, spectrum management, civil aviation) and modern software engineering. Today I focus on turning that domain depth into LLM-powered systems: multi-agent diagnostic pipelines, grounded retrieval over dense technical corpora, and deterministic engineering tools wired into agent loops.

I care about systems that don't hallucinate, always terminate, and can be audited — not demos that fall apart outside the happy path.


🛠️ What I work with

AI / LLM LangGraph · LangChain · RAG · ChromaDB · Ollama (local LLMs) · DeepSeek · Qwen2.5 · Pydantic structured outputs · citation-verified retrieval

Backend Python · FastAPI · async / SSE streaming · SQLite · InfluxDB · SNMP / PySNMP

Frontend Flutter · Dart (cross-platform desktop & web)

Domain Satellite / VSAT network operations · ITU Radio Regulations · spectrum & frequency coordination · NOC / AIOps


🚀 Featured Projects

A domain-specific AI agent for satellite frequency coordination, grounded in the ITU Radio Regulations. A LangGraph multi-agent pipeline (Router → Researcher → Calculator → Citation Verifier → Critic → Synthesizer) runs over a ChromaDB store of provision-level chunks, calls deterministic engineering tools (link budget, ITU-R P.618 rain attenuation, P.676 gaseous absorption, coordination triggers), and answers with verifiable citations to specific RR provisions. LangGraph · RAG · ChromaDB · FastAPI · Flutter

A multi-agent LLM diagnostic assistant for satellite NOCs, designed to run fully offline in air-gapped environments. An 8-node LangGraph state machine extracts symptoms, retrieves candidate diagnoses via RAG, gathers evidence through SNMP-style tools, scores candidates, and runs a self-critic node as an anti-hallucination guardrail — all on local Qwen2.5 via Ollama, no cloud calls. LangGraph · Ollama · RAG · Air-Gapped · FastAPI · Flutter

An asynchronous monitoring platform for Juniper EX2300 switches: real-time SNMP telemetry, L2 loop / broadcast-storm detection with source-vs-victim isolation, and historical trend analysis. Python/FastAPI backend with circuit-breaker resilience + a Flutter NOC dashboard. SNMP · FastAPI · InfluxDB · Flutter · Network Automation


📫 Get in touch

I'm currently open to remote roles in Senior AI Engineering, RAG / LLM systems, agentic workflows, and Flutter. If you're building agentic systems for regulated industries, air-gapped networks, or technical/engineering domains, I'd love to talk.

📧 mmwady@gmail.com · 💼 LinkedIn · 🌐 Portfolio

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  1. itu-rr-assistant itu-rr-assistant Public

    Domain-specific AI agent for ITU satellite frequency coordination — LangGraph multi-agent RAG over the Radio Regulations with deterministic link-budget and interference tools, cited to specific pro…

    Python

  2. ai_noc_assistant ai_noc_assistant Public

    Offline-first multi-agent LLM diagnostic assistant for air-gapped satellite NOCs — LangGraph 8-node agent pipeline + local Qwen2.5 + RAG, with a self-critic anti-hallucination guardrail.

    Dart

  3. Juniper-NOC-Dashboard-Monitoring-System Juniper-NOC-Dashboard-Monitoring-System Public

    Async NOC monitoring for Juniper EX2300 — SNMP telemetry, L2 loop/storm detection with source-vs-victim isolation. FastAPI + Flutter.