AI Architect

Sovereign AI architecture for regulated banks in the UAE.

AI Architect. I own end-to-end RAG and agentic architecture on sovereign cloud infrastructure: model-agnostic, audited, and running in production for core banking.

// a sovereign, model-agnostic AI architecture for regulated banking
18+ yrssoftware architecture, across banking, aviation, security, embedded
Production GenAIRAG + LLM features live in a core banking suite
Model-agnosticfrontier ↔ open-source, swappable without rewrites
Sovereign by designdata residency and audit built in, not bolted on

Don't take my word for it. Check it.

Look. Anybody can write "banking AI expert" on a website. Here is what you can verify yourself, today.

  1. A citable checklist with a DOI. The LLM red-teaming checklist for banking is archived on Zenodo: 10.5281/zenodo.23536860, released 21 Oct 2026, source on GitHub.
  2. A working scorer, not a slide. The LLM Red Teaming for Banking Severity Scorer runs on Hugging Face. Nine harm categories (seven mapped to the OWASP LLM Top 10 2025).
  3. The article Google puts first. LLM red teaming for banking in the UAE ranked #1 on Google UAE for "LLM red teaming for banking" on 23 Oct 2026.
  4. A named failure mode. Borrowed Clearance: when a bank's AI agent moves money based on a check it didn't run and can't verify. Coined by Ercin Dedeoglu, 21 Oct 2026.

What I do

I design the architecture that lets enterprises run generative AI in environments where mistakes are not an option. I do this as an AI architect in Dubai, for banks across the UAE, where data residency and DIFC/CBUAE expectations shape the design. That means provider-agnostic LLM gateways, retrieval and agentic patterns that survive production load, and governance — observability, audit trails, human-in-the-loop — treated as first-class, not afterthoughts. My background is low-level: reverse engineering and systems work. I bring that precision to AI platforms.

Building AI for a regulated environment? Let's talk architecture.

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