Farouk BENSALAH

AI Engineer | LLM • RAG • FastAPI | Open to Work

Salaire / Taux journalier

Tunis, Tunisie

Freelance, ouvert au CDI

Expertises

PythonFastAPILLMs / Large language modelsTensorFlowJavascriptRequêtes SQLDeep LearningData AnalysisBig DataIAMachine LearningPyTorchOracle DatabaseJavaNLP / Natural Language ProcessingDockerscikit-learnKerasMySQLMongoDBCassandraApache SparkHadoopKafkaLaravelRESTful APIsReactCoaching agileScrum

Langues

Arabe (Maternelle)Anglais (Courant)Français (Courant)

À propos

Introduction

🚀 Generative AI Engineer | LLM • RAG • FastAPI | Open to WorkComputer engineer specialized in Big Data & AI (Master’s level, Polytechnique Internationale de Tunis), focused on building production-ready AI systems: LLM assistants, multi-tenant RAG pipelines, fine-tuning and secure AI APIs.Latest project: end-to-end design of a business AI assistant integrated into a SaaS platform (RoundGRC) — microservices architecture, multi-tenant RAG with ChromaDB, LoRA/QLoRA fine-tuning via Ollama, anti-hallucination guardrails and FastAPI with SSE streaming.Core skills:🔹 LLM, RAG, Agentic AI, Prompt Engineering, LLM Evaluation🔹 LangChain, LlamaIndex, Hugging Face, Ollama, ChromaDB🔹 FastAPI, Docker, CI/CD, AWS, MLflow🔹 PyTorch, TensorFlow, YOLOv8, Scikit-learnHybrid AI / Backend / MLOps profile — I cover the full AI project lifecycle, from business requirements to production deployment.📍 Tunis, Tunisia — Open to remote / international relocation📩 [email protected]

Liens

Expérience de travail

AI / LLM Engineer

Roundesk

févr. 2026 - juil. 2026

6 mois

Sousse, Tunisie

Designed and developed a business AI assistant integrated into RoundGRC, a SaaS customer support platform, serving multiple clients in a strict multi-tenant architecture. 🔹 Built a complete microservices architecture: runtime orchestrator, RAG service, LLM service, channel service and document management layer. 🔹 Designed a multi-tenant RAG system with per-client document isolation, multilingual embeddings, ChromaDB vector store and reranking for improved answer relevance. 🔹 Fine-tuned a local LLM via Ollama using LoRA / QLoRA, reducing inference costs while improving contextual response quality. 🔹 Built secure AI APIs with FastAPI: JWT authentication, SSE streaming and structured responses. 🔹 Implemented anti-hallucination guardrails to keep responses grounded in document context. 🔹 Delivered: automatic correction, professional rephrasing, contextualized response suggestions and streaming generation.

Stagiaire

STEG Tunisie

juil. 2024 - août 2024

2 mois


Formation

Ecole Polytechnique Internationale

Ingénieur Big Data, BI & IA, Ingénierie informatique

2021 - 2026

4 ans 11 mois


Licences et certifications

Information Technology Specialist in Java

Délivré le : mai 2024

Certifié par Information Technology Specialist

Information Technology Specialist in JavaScript

Délivré le : avr. 2024

Certifié par Information Technology Specialist

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