⚙️ Backend & AI Engineer  |  🎓 CCE @ Alexandria University  |  ☁️ AWS & MLOps Explorer

"Building the invisible infrastructure that makes intelligent systems possible."

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🧠 About Me

class AmrKhaled:
    role       = "Backend & AI Engineer"
    education  = "Computer & Communication Engineering @ Alexandria University"
    location   = "Egypt 🇪🇬"

    expertise  = [
        "Backend Engineering & API Design",
        "AI/ML Systems & Model Deployment",
        "Cloud Architecture (AWS)",
        "Distributed Systems & MLOps",
    ]

    current_focus = [
        "Building production-grade ML inference pipelines",
        "Designing scalable microservices architectures",
        "LLM integration & RAG systems",
        "Advanced system design & distributed patterns",
    ]

    goal  = "Architect intelligent, scalable backend systems that power real-world AI products"
    motto = "Good code scales. Intelligent systems evolve."

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💡 Core Competencies

⚙️ Backend Engineering RESTful & GraphQL API design Microservices & event-driven architecture Database design & query optimization Caching strategies (Redis, CDN) Authentication, authorization & API security Rate limiting, logging & observability	🤖 AI & ML Engineering Neural network design & training (PyTorch) ML model deployment & serving (FastAPI, TorchServe) LLM integration & RAG pipelines MLOps: experiment tracking, model versioning Computer vision & NLP applications Feature engineering & data pipelines
☁️ Cloud & DevOps AWS (EC2, Lambda, S3, RDS, SageMaker) Docker & container orchestration CI/CD pipelines (GitHub Actions) Serverless & infrastructure as code Cloud cost optimization Monitoring & alerting	📐 System Design Distributed systems & consensus patterns CQRS & event sourcing Message queues (Kafka, RabbitMQ) High-availability & fault-tolerant design Database sharding & replication API gateway & load balancing strategies

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🛠️ Technology Stack

Languages

Backend & Frameworks

AI / ML & Data

Cloud & DevOps

Databases & Messaging

Tools

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📊 GitHub Statistics

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🎯 Current Learning Path

🧭 Area	📚 Focus
AI Engineering	LLM fine-tuning, RAG pipelines, vector databases (Pinecone, Weaviate)
MLOps	MLflow, model monitoring, A/B testing, drift detection
Cloud Architecture	AWS Solutions Architect, SageMaker deployment, multi-region systems
System Design	Distributed systems, event sourcing, CQRS, Kafka-based architectures
Algorithms	LeetCode, NeetCode 150, competitive programming

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📫 Let's Connect & Collaborate

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⚡ "Build backends that don't just serve requests — they power intelligence." ⚡