Mehdi Neggazi

I am a DevOps-oriented software engineer and systems architect with a strong focus on building reliable, automated, and scalable infrastructures that bridge modern cloud platforms with real-world operational needs.

My work sits at the intersection of software engineering, infrastructure automation, and distributed system design. I design and implement systems that are production-ready, observable, and resilient—often starting from low-level Linux and networking fundamentals and extending upward into cloud-native architectures and AI-driven workflows.

Core Expertise

I have hands-on experience designing and operating systems across the full stack, including:

DevOps & Infrastructure

• Linux system administration, process management, networking, and security hardening
• Docker, container orchestration, and multi-service deployments
• CI/CD pipelines, environment isolation, and reproducible builds
• Cloud platforms with a strong focus on AWS services (IAM, EC2, S3, DynamoDB, networking, monitoring)

Backend Engineering & Automation

• Node.js, Python, and TypeScript for backend services, automation scripts, and APIs
• Event-driven systems, job queues, background workers, and real-time data flows
• WebSockets, SSE, and streaming architectures for low-latency applications
• Integration with third-party APIs and legacy systems

System Design & Architecture

• Designing modular, service-oriented architectures with clear boundaries
• Data modeling for SQL and NoSQL systems, with attention to scale and access patterns
• Observability: structured logging, metrics, error tracking, and runtime diagnostics
• Security-aware design: authentication flows, secrets management, and access control

AI & Agentic Systems

• Building AI-powered tools and automation pipelines
• Designing agent-based systems with tool access, retrieval (RAG), and streaming outputs
• Integrating LLMs into production workflows rather than isolated demos

Engineering Philosophy

I approach engineering with a systems mindset:

• I value clarity over complexity and prefer designs that are easy to reason about, debug, and extend.
• I prioritize automation, eliminating manual steps wherever possible.
• I believe infrastructure should be observable by default—if you can’t see it, you can’t trust it.
• I treat DevOps not as tooling, but as a discipline that connects code, infrastructure, and operational reality.

I am comfortable working close to the metal when necessary (Linux, networking, processes) and equally comfortable designing higher-level abstractions when scale and maintainability demand it.

Current Focus

My current work involves:

• Advanced DevOps automation and cloud certification (AWS-focused)
• Designing real-time, AI-augmented backend systems
• Building scalable internal tools that reduce operational overhead
• Exploring agentic architectures that combine AI, automation, and system observability