Resume

One of two founding engineers at an early-stage AI platform automating guest communication and property operations for short-term rental operators (San Francisco & London), backed by a $1M seed round led by Revo Capital (announced February 2026).

• Held primary ownership of the web and mobile product surfaces as one of two founding engineers — 84.7% of surviving frontend code by sampled git blame, and every commit ever made to the iOS and Android projects.
• Rebuilt the young web codebase as its primary author into a 93-component design system spanning 27 product areas and 13 locales including Arabic right-to-left, and released both native apps across Capacitor, Firebase push, and over-the-air updates (React 18, TypeScript, Vite, Redux Toolkit).
• Built the surfaces operators run the product through — Agent Hub configuration, knowledge base and rule authoring, onboarding, the unified inbox, workflow builder, scheduling, task management and payment flows — and contributed to the channel and PMS connection screens.
• Built the product layer for the company's AI capabilities and the transport beneath it (AG-UI, server-sent events, SignalR), integrating the team's LangGraph services and RAG pipelines into the product.
• Acted as the integration point at the production gate as the contributor base widened, carrying multi-author frontend changes into production — 377 releases coordinated across four repositories under 17 runbooks I wrote.
• Owned the notification and real-time system end to end (.NET, SignalR, server-sent events, Firebase Cloud Messaging), cutting unnecessary push traffic by an estimated ~19,000 notifications/day, extrapolated from a production telemetry sample.

Maya — an AI career agent: candidates don't apply, they get interview invites, matched through a dual-agent hiring network (London-registered, distributed team).

• Made the first commit to the web application and went on to author roughly three quarters of it (157 of 209 commits) — the substance behind "founding frontend engineer."
• Built the candidate experience of Maya, ReadyFly's AI career agent — conversational onboarding and the job-pitch review flow through which candidates approve interview invites.
• Implemented the dual-agent landing readyfly.io serves today, including its seven-state auto-playing demo of a role being matched and an interview confirmed.
• Enforced GDPR/ePrivacy consent technically — no non-essential script executes before consent — without a paid consent-management platform.
• Built the live interview surface of the earlier hiring-platform MVP: real-time video over LiveKit, an embedded Monaco code editor, and proctoring running concurrently in one session.
• Contributed to the FastAPI API, including the microservice decomposition separating CV ingestion, authentication and profile services, and integrated the team's AI matching into the product surfaces.

• Designed the backend architecture using .NET Core (Onion Architecture), PostgreSQL, and Python.
• Designed the frontend architecture using Next.js and React.
• Reduced API latency by 45% via Redis caching and query optimisation.
• Implemented secure authentication using Identity Server, JWT, and OAuth2.
• Built real-time systems using SignalR, WebSockets, and server-sent events.

• Worked as a fullstack developer across ATS (vehicle management), GTS (task management), a real-estate system and several sub-projects — one team carrying five to six concurrent projects.
• Operated inside kanban/scrum cadences with per-sprint performance scoring — the period that turned discipline from a habit into a method.
• Built scalable frontend systems with React and Next.js, including PWA capabilities.
• Designed and implemented backend services with .NET Core using clean architecture principles.
• Integrated external services and APIs, including Google services and third-party libraries.

Volunteer AI and machine-learning work alongside full-time roles, on Interfarm — Interno's closed vertical-farming R&D venture at Ankara University Teknopark, funded under TÜBİTAK's competitive 1501 industrial R&D programme (Digital Agriculture call).

• Named in the funded proposal as the project's Data Scientist — the only person listed against its AI development, machine-learning and algorithm work.
• Built the fuzzy-logic control layer that decides the growing module's climate, nutrient and lighting behaviour (Python, with membership functions modelled in MATLAB), and built the browser-based HTML5 operator application end to end.
• Worked against a Raspberry Pi automation unit per module, CANBUS on the unit and MQTT off it, into a Linux server running SQL Server, Python and Node-RED.
• The company reports the proposal ranked first among roughly 300 applications in its call — a company-reported figure, not one I verified.
• Built machine learning pipelines using Python, NumPy, Pandas, and Scikit-learn.

• Volunteered to independently design and develop Actio's promotional landing page, including its content presentation and animations, beyond my initial IT remit. Milapasa's development team built the event-management application.
• Represented Actio in the field and moderated its live events — travelling ahead with the team to set venues up, running QR-code check-in together, and hosting international project managers.
• Worked within WEglobal's IT infrastructure through Milapasa's strategic partnership — help-desk to field support, from machine setup to travelling to resolve problems at their source.
• Kept programme data consistent and presented it through PowerBI across EU-funded programmes; administered and supported their monitoring-and-evaluation portals.
• Built an internal e-learning portal, including learning objects and lesson activity plans; administered CRM/ERP systems, worked with MySQL data, and provided technical support.