10+ years shipping production Android · Currently leading mobile at SSS Sports (Nike, Under Armour, Sun & Sand Sports)
I'm a Senior Android Engineer and Technical Lead with 10+ years of experience building consumer-grade mobile products at scale. My current work spans the Nike, Under Armour, and Sun & Sand Sports apps across the UAE — products used by millions of shoppers across the GCC.
Lately I've been leaning hard into AI-augmented engineering: building RAG pipelines, MCP servers, and multi-agent systems that plug directly into mobile workflows. I use Claude Code, DeepSeek, and GitHub Copilot daily, and I treat LLM tooling as a first-class part of the stack.
- 🏗️ Architecture nerd — Clean Architecture, MVI, feature-first modules, Riverpod codegen
- 🤖 AI Engineer — RAG (89% faithfulness), LangChain, LangGraph, CrewAI, Pinecone, FastAPI
- 📱 Cross-platform — Native Android (Kotlin + Compose) + Flutter/Dart
- 🌍 Based in Dubai · open to senior & lead roles across the GCC
A production-grade e-commerce Android app built with Kotlin + Jetpack Compose + Clean Architecture. Demonstrates unidirectional data flow, modular feature structure, and modern Compose UI patterns. → View repo
An internal LLM-powered chatbot integrating DeepSeek with a TypeScript backend to deliver editorial product recommendations across Nike, Under Armour, and Sun & Sand stores. Custom JSON schema, streaming responses, and system-prompt engineering for brand voice consistency.
AI-generated client status digests from Git activity. Parses commits → generates plain-English sprint summaries → delivers via email. Built for dev agencies who need transparent async client updates without extra overhead. Stack: TypeScript · GitHub API · Claude API · LemonSqueezy
A retrieval-augmented generation system with sub-100ms query latency. Embeddings indexed in Pinecone, retrieval orchestrated via LangChain, served through FastAPI. Evaluated with RAGAS achieving 89% faithfulness score.


