I spent three years at DubizzleLabs on the systems behind Zameen.com, Bayut.sa and Propforce:
distributed Node.js/TypeScript services, transactional data at real volume, and the unglamorous work that keeps
them fast (query plans, indexes, background workers, observability, RBAC).
Then I built the layer above. AVA, an internal AI copilot that takes a request in chat all the way
to a reviewed pull request. MCP servers that give LLM agents typed access to internal APIs instead of
engineers digging through docs. A RAG knowledge base over architecture decisions that answers in plain English.
None of it was a demo. Colleagues used it every day.
I'm now doing an M.Sc. in Computer & System Engineering at TU Ilmenau, researching a
data-integrity layer for LangChain QnA systems: blockchain-anchored fingerprints re-verified at inference time,
so a poisoned corpus can't quietly answer for you.
Since August I've been a Forward Deployed Engineer at UnternehmerTUM's Venture Lab in Munich,
which is the fastest version of this work I've done. I get dropped into a product team and the job is to get
something usable out in days: an app for validating venture AI use cases, tooling for checking work against AI
policy and EU AI Act criteria, internal apps that pull scattered org processes into one place.
What ties it together is simple enough. I want the thing I build to end up in someone's daily workflow, which
is what I aim for at the Venture Lab and in the projects I build on my own time.