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Rami I. Backend, AI and General Development

My name is Rami I. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: Python, SQL, Django, Graph, Data Structures, etc.. I hold a degree in Engineer's degree, Bachelor of Computer Science (BCompSc). Some of the notable projects I’ve worked on include: LinkedIn automation & Personalized email sequencing, Real-Time Chatbot for Tenant-Owner Communication, n8n-based WhatsApp bot (Saudi Arabian Dialect), Customize PrivateGPT for production usage (AI, AI Customer Support Agent on Discord (RAG, ChromaDB, Feedback Loop), etc.. I am based in Tunis, Tunisia. I've successfully completed 15 projects while developing at Softaims.

My passion is building solutions that are not only technically sound but also deliver an exceptional user experience (UX). I constantly advocate for user-centered design principles, ensuring that the final product is intuitive, accessible, and solves real user problems effectively. I bridge the gap between technical possibilities and the overall product vision.

Working within the Softaims team, I contribute by bringing a perspective that integrates business goals with technical constraints, resulting in solutions that are both practical and innovative. I have a strong track record of rapidly prototyping and iterating based on feedback to drive optimal solution fit.

I’m committed to contributing to a positive and collaborative team environment, sharing knowledge, and helping colleagues grow their skills, all while pushing the boundaries of what's possible in solution development.

Main technologies

  • Backend, AI and General Development

    2 years

  • Python

    1 Year

  • SQL

    1 Year

  • Django

    1 Year

Additional skills

Direct hire

Potentially possible

Previous Company

Sofrecom

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Experience Highlights

LinkedIn automation & Personalized email sequencing

Led the development of two key pipelines: - LinkedIn automation - Personalized email sequencing Coordinated with two AI developers, managed task assignments, and ensured smooth execution from start to finish. Designed a personalization engine powered by OpenAI structured outputs, LangChain, and custom prompt templates. Each email was dynamically tailored based on the lead’s role, company, and interaction history from Apollo data.

Real-Time Chatbot for Tenant-Owner Communication

Developed AI Assistant, a smart chatbot designed to monitor and respond to real-time tenant–owner message threads. The bot detects repetitive queries, understands user intent, and responds autonomously. Key Features: - Implemented custom logic to detect tenant intents (rent status, maintenance, contract details). - Used OpenAI structured output to extract key entities from messages. - Automatically replies to frequent/repetitive queries with context-aware responses. - Enabled Owner review and correction to continuously improve bot accuracy.

n8n-based WhatsApp bot (Saudi Arabian Dialect)

Developed a fully automated WhatsApp chatbot built on n8n that understands and responds in Saudi Arabian dialect, handling both text and audio messages. The bot intelligently engages users to collect essential client information, answer FAQs using RAG with Pinecone, and integrates seamlessly with Kommo CRM and an internal portfolio database. Key Features : - Processed both voice messages (audio-to-text) and text queries. - Implemented Retrieval-Augmented Generation pipeline with Pinecone vector DB. - Added tool-calling logic to query internal databases when needed (for portfolio).

Customize PrivateGPT for production usage (AI|NLP|RAG|LLAMA|DEEPSEEK)

This project involved transforming an open-source codebase into a reliable, user-friendly, and scalable tool ready for production use. Key Features : - Debugged and stabilized multiple ingestion pipelines (YAML, XLSX, JSON, Auto-upload). - Integrated TREE_SUMMARIZE for structured summarization. - Enabled DeepSeek-style “thinking” model behavior through refined context windows and token stream control. - Migrated UI from Gradio 4.x to 5.x for improved layout, theming, and usability. - Optimized hardware utilization through multiprocessing and worker configuration.

AI Customer Support Agent on Discord (RAG, ChromaDB, Feedback Loop)

Developed and deployed Scouty, a smart AI customer support agent , integrated into Discord. Scouty was trained on thousands of historical support tickets and designed to autonomously handle new user queries using RAG, fine-tuned LLMs, and a structured feedback learning loop. Key Features : - Implemented a ChromaDB-based vector search system to index cleaned historical tickets. - Included metadata filtering to match product versions, topics, and response tone. - Built a fully functional Discord bot that listens for new support messages. - Feedback Learning Loop (logged every interaction)

Education

  • Institut Superieur d'Informatique et Mathématique

    Engineer's degree in software engineering

    2021-01-01-2026-01-01

  • Lycée mhamdia

    Bachelor of Computer Science (BCompSc) in Computer science

    2020-01-01-2021-01-01

Languages

  • Arabic
  • English
  • French

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