YorgoTabet

Wallet-as-a-Service SDK(React Native, iOS, Android, Flutter, Web)

• Built a shared SDK for one of Saudi Arabia's largest banks, packaging common bank flows (transactions, cards, authentication and authorization, contact and location access) across iOS, Android, Flutter and web for 3 products serving 3.5M+ users, built by 15+ developers
• Took per-team setup, integration and repeated requirements explanation from roughly 8 sprints to 2-3 days by shipping a configuration guide
• Built a library-agnostic layer separating app components from the third-party libraries underneath, turning a dependency swap from a multi-sprint refactor into days
• Integrated the bank's internal design-system platform, twelve packages in all, into production applications
• Defined and maintained logging, tracking and crash-reporting standards using Dynatrace, Splunk and Firebase

Relationship Manager Workbench & Mortgage Platform(React, Redux, Java Spring)

• Developed internal platforms standardized across all 226 Riyad Bank branches, serving relationship managers and mortgage teams on a 115,000-line codebase
• Implemented a fully configurable dynamic table system full-stack using the factory pattern, removing ~75% of repetitive UI code
• Improved load times up to 90% and took CI pipeline duration from 45 to 15 minutes through test parallelization and targeted caching
• Documented a 100,000-line mortgage codebase, cutting new-joiner onboarding from two engineers spending a sprint to a single session
• Implemented the authentication and authorization flows behind both platforms

Kids E-Banking(React Native)

• Owned biometrics, authentication and code optimization on a kids e-banking app, cutting mobile API calls by ~50% with client-side caching and request de-duplication

Online Mortgage(ReactJS)

• Led requirements planning, set review standards, documented features and infrastructure, and supported onboarding of new team members

API Management Platform(ReactJS)

• Defined frontend architecture and implementation approach; enforced testing and CI quality gates to support parallel delivery

AI-driven Decision Support Platform(ReactJS, FastAPI, Python, Redis, MongoDB)

• Designed a queue-based processing model to handle concurrent AI workloads, reducing failure rates from about 50 percent to around 10 percent through retries and database-backed state management
• Implemented event-driven communication between backend and frontend to surface real-time processing status in the UI
• Owned frontend development for more than 10 modules covering audio and video workflows, prompt editing, and feedback loops
• Built and maintained audio and video summarization and content generation pipelines used for reports and recommendations
• Improved system reliability by ensuring queued and in-flight jobs survived outages and service restarts

AI Executive-Support Platform(React, TypeScript, FastAPI, CrewAI, Redis, Qdrant)

• Led development of a multi-agent AI platform for a government executive office, cutting ministerial planning preparation from weeks to around 30 minutes
• Streamed per-stage progress and plain-language failures in place of static loaders, after users said they could not tell what was running
• Improved AI agent chat orchestration, cutting model calls by 50% per message by replacing a per-reply planner with a scoped context agent
• Designed an agentic mapping and normalization flow for Excel data, with a shared vocabulary for model learning and human correction
• Wrote the team's AI coding standards, 7 rules and 14 skills, taking a feature from whole-team effort to one developer
• Unified those skills across Cursor, Claude Code and Copilot behind one canonical folder and a committed symlink, with a lint gate on changed lines and decisions written once and loaded by every agent
• Cut stored document volume by ~30%, holding uploads in draft until processing succeeded and sweeping orphans automatically
• Wrote the API specs two external government systems are now built against, cutting field lists to 16 of 32 and 14 of 20 across 4 rounds
• Integrated Microsoft Graph for calendar and mail ingestion, and grounded chat in the supporting documents

Investment Feasibility Platform(React, Python, Azure)

• Delivered an AI-augmented platform for the firm's own consulting teams, automating the research and financial modelling behind feasibility studies on projects worth millions to billions
• Gated accuracy to 0.5% with CI checks that fail on regressions, holding parity between the platform's calculations and the consultants' Excel models
• Built human-in-the-loop correction so each study's adjustments feed into the next
• Held data quality with guarded AI search and a RAG knowledge base over previous studies, exposing only the levers a consultant should adjust
• Delivered it as a containerized service on Azure Kubernetes, with SSO-gated access for internal users

Economic Estimation Automation(Python, Oracle Cloud Kubernetes)

• Automated gross-value-added estimation pipelines in Python, replacing manual, spreadsheet-driven estimation work with a repeatable pipeline
• Deployed the pipeline as a containerized service on Oracle Cloud Kubernetes, covering scheduling, execution, and output delivery

B2B Procurement Platform(Xamarin, .NET Core)

• Implemented WhatsApp integration across mobile, backend, and provider services; participated in code reviews and internal coding standards