AI Engineer · GenAI · RAG · Agents

Building production-ready AI systems.

I am Mohamed Elsayad, an AI Engineer focused on RAG pipelines, LLM applications, agentic systems, and AI automation with n8n. I turn complex ML ideas into practical, reliable products.

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5+ AI projects

Cloud AWS & Azure certified

GenAI RAG, agents, automation

About

AI engineering with product impact.

Microsoft-Certified AI Engineer specializing in NLP, LLMs, Generative AI, and AI agents. Experienced in RAG systems, AI automation with n8n, and deploying scalable AI solutions on Microsoft Azure and modern backend stacks.

I care about practical delivery: clean APIs, reliable inference pipelines, measurable outcomes, and systems that engineering teams can maintain after launch.

Core Expertise

What I deliver

End-to-End GenAI

LLM-powered applications with clean APIs, secure workflows, and production-oriented architecture.

RAG Systems

Retrieval pipelines, vector databases, chunking strategies, hybrid search, and evaluation-ready designs.

Agentic Workflows

Autonomous agents, tool use, orchestration flows, and guardrails for practical business automation.

AI Automation

n8n workflows that connect AI models with real business processes, data sources, and notifications.

Featured Work

Selected AI projects

GenAI Platform

CHAT-PLUS

Enterprise-grade GenAI service hub with multi-backend LLM inference, real-time WebSocket chat, and RBAC security.

Supports vLLM and Ollama backends
Real-time chat architecture
Role-based access controls

FastAPI vLLM WebSockets

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RAG Platform

Evolved-RAG

Scalable RAG platform with LangChain and Qdrant, supporting hybrid search, multi-provider LLMs, and observability.

Vector search with Qdrant
Multi-provider LLM support
Monitoring-ready architecture

RAG Qdrant LangChain

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LLM Fine-Tuning

ArNews Fine-Tuning

Fine-tuning Qwen-1.5B on Arabic datasets with LoRA, synthetic data generation, and experiment tracking.

Arabic NLP model adaptation
LoRA fine-tuning workflow
W&B experiment tracking

Qwen LoRA NLP

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Healthcare AI

Brainpulse

EEG signal classification system using deep learning to support clinical diagnostics workflows.

91% classification accuracy
PyTorch model pipeline
Signal processing workflow

PyTorch EEG Deep Learning

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NLP Analytics

Customer Sentiment Analysis

End-to-end NLP pipeline for analyzing customer feedback and turning text data into business insights.

Text preprocessing pipeline
Sentiment classification
Business insight reporting

NLP Analytics Python

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Technical Stack

Skills grouped by impact

Generative AI & LLMs

OpenAI SDKAnthropic SDKOllamaRAG SystemsPrompt EngineeringContext EngineeringLLM Evaluation

AI Agents

Tool CallingMCPMulti-Agent SystemsAgent OrchestrationLangChainLangGraphCrewAIAutoGen

NLP

TransformersHugging FaceSentence TransformersSemantic SearchNERText ClassificationEmbeddings

Computer Vision

OpenCVYOLOMediaPipeOCRObject DetectionImage ClassificationVision Transformers

Machine Learning

PyTorchTensorFlowScikit-learnFeature EngineeringModel TrainingHyperparameter TuningModel Evaluation

Backend Engineering

FastAPIREST APIsSQLAlchemyAlembicAuthenticationAuthorizationRate LimitingWebSocketsAsync ProgrammingBackground JobsCelery

Databases & Vector Stores

PostgreSQLMySQLMongoDBRedispgvectorQdrantPinecone

Cloud Computing

AWSAzure

DevOps & Monitoring

NGINXRabbitMQvLLMGitHub ActionsCI/CDPrometheusGrafanaLinux

AI Automation

n8n

Experience

Professional experience

June 2026 - Present

AI Engineer · ReNile

Agriculture company

Building AI solutions for agricultural technology, with a focus on practical systems that support data-driven workflows, automation, and scalable AI product development.

Credentials