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ahmedabushawis

Ahmed A

@ahmedabushawis

Computer Engineering Graduate AI Digital Strategy Intern

Emiratos Árabes Unidos
Inglés, Árabe
Parte de la información aparece en idioma inglés.
Sobre mí
I am a Computer Engineering graduate based in Dubai, currently working at AG&P LNG where I build AI tools that automate real business processes. I enjoy the full journey of a product: understanding the problem, designing the system, and shipping something people actually use. I have extensive experience in SQL, Python, and building end-to-end LLM pipelines.... Lee más

Habilidades

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ahmedabushawis
Ahmed A
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Revisa mis servicios

Implementación y despliegue de IA
I will build you a custom automation or business dashboard

Experiencia laboral

AGP_MEDIA

Intern, AI & Digital Strategy

AGP MEDIA • Tiempo completo

Apr 2026 - Present • 6 mos

Built an end-to-end RFP automation agent: it drafts procurement documents, sends them out to vendors, collects submissions, and scores every proposal against the others, cutting vendor evaluation time from 3-5 days down to under 2 hours per RFP while handling ~5 RFPs and 15-25 vendor submissions per month. Built an internal AI command platform for the chairman of a multi-business holding group, centered on an AI Decision Queue that reads through emails and meeting transcripts across three separate businesses, automatically surfacing decisions and follow-ups and assigning them to the right person so nothing gets missed or forgotten. Expanded that same command platform with an automated daily briefing and monitoring layer that checks email every 15 minutes and reviews calendars and meeting notes on a schedule, only calling the AI when there is actually something new to review, keeping the platform fast and cost-efficient. Deployed this command platform on Microsoft Azure with a fully separate staging environment and secured it with two-factor authentication, so new features could be tested safely before reaching the chairman relying on it every day.

SyncroB

AI/ML Developer

SyncroB • Tiempo parcial

May 2025 - Feb 2026 • 9 mos

Designing an LLM-powered IoT assistant that automates smart-building control and scheduling through natural-language interaction. Implementing LangGraph-based architectures to interpret user intent and dynamically generate structured API calls for device management, scenes, and schedules. Integrated context-aware reasoning using user preferences, device metadata, and environment data to personalize responses and improve automation accuracy. Optimized backend communication pipelines, reducing API response latency and improving system scalability for multi-tenant environments. Collaborated with the backend and product teams to define data schemas, routines, and context-gathering layers for the assistant’s memory and long-term learning. Integrated diagnostic dashboards and performance monitors that cut debugging time by 40% and increased visibility across the IoT ecosystem