The AI Security Engineer Career Masterclass

About this course

The cybersecurity industry is entering a new era.

For years, security professionals have focused on protecting applications, infrastructure, identities, and data from attackers. But AI is changing how applications are built, how they interact with information, and increasingly, how they make decisions and execute actions.

Modern AI applications are no longer limited to simple chatbots.

They use Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), external APIs, Model Context Protocol (MCP), and autonomous AI agents to interact with business systems and perform real-world tasks.

An AI assistant might retrieve confidential company documents, access employee records, create support tickets, or execute actions in a cloud environment.

But what happens when an attacker manipulates the information an AI system receives? What if an AI agent invokes an unauthorised tool, exposes sensitive information, or performs actions that were never intended?

This is where AI Security Engineering comes in.

AI Security Engineering is an emerging cybersecurity discipline focused on understanding, assessing, testing, and securing modern AI applications.

It combines traditional cybersecurity principles such as application security, identity, access control, cloud security, and threat modeling with new challenges including prompt injection, RAG poisoning, insecure MCP integrations, excessive agency, and autonomous AI behaviour.

The AI Security Engineer Career Masterclass is a practical, hands-on course designed to help cybersecurity professionals, software developers, cloud engineers, students, and career changers develop the skills needed to assess and secure real-world AI applications.

You will learn how modern AI systems are built, where their security weaknesses exist, how attackers exploit them, and how to design controls that reduce those risks.

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