AI Systems Engineer · Egypt → EU & US
I build, ship, and operate multi-agent AI systems for businesses that can't afford to wait.
3 live products. 2 open-source tools. Every hard lesson published with real numbers.
I'm Omar — a senior AI systems engineer based in Egypt, serving clients across the EU and US. I build multi-agent production systems — the kind that qualify leads, forecast demand, and operate autonomously. Not demos that break after the investor meeting.
Three live products with paying customers. Two open-source tools. Two published essays with real production numbers. Nine years of full-stack engineering across MENA, with the last two focused on shipping AI into consumer-facing products: retail ops, exam prep, B2B sourcing.
I sit at the intersection most engineers avoid: code, marketing, and operations. The MENA AI market is starving for people who actually ship working systems instead of slide decks. That's what I do — from Egypt's cost structure, at senior-level quality, with native Arabic and EU timezone overlap.
From computer vision prototypes to multi-agent AI fleets — every mission built on the last.
Six autonomous products. Designed to run without me — from AI retail to open-source agent memory.
Full case studies with architecture diagrams and real numbers. Technical essays with per-change contribution breakdowns. An interactive sandbox of my open-source agent memory project. This is the section I'd send to someone who asked "but can he actually ship."
Six specific moves — task routing, semantic caching, prompt compression, structured output, batching, waste gatekeeping — with per-change contribution numbers.
Read the essay → Essay · 9 minA production LLM extraction pipeline at Bridge Sourcing went from 82% to 96% over three months. The eight changes, and the two that made it worse.
Read the essay → Case studyPaying customer in Egypt. ~4% MAPE forecasting, 218ms POS sync, what-I-got-wrong section, SVG architecture diagram.
Read the case study → Case study7,725 questions, Telegram Mini App, the explanation pipeline that turns testing into teaching.
Read the case study → Case studyEU buyers ↔ Egyptian suppliers. Three agents, one rubric that does most of the work.
Read the case study → Interactive LabStore memories, watch auto-classification, run semantic queries, see contradictions flagged. Pure client-side, no API calls.
Open the sandbox →Six autonomous products. Multi-agent pipelines running 24/7. Cost-optimized LLM routing. This is what operating at scale looks like from the cockpit.
These three tools exist because I use them in my own work. They're not a funnel — no email capture, no tracking, no "send to Omar" buttons in the outputs. If you find them useful, use them. If not, keep scrolling to the work that matters.
Building AI systems, exploring new missions, or just want to talk autonomous agents — I'm reachable across all frequencies.