Outcomes
Where CN-CAISE takes you
The roles this prepares you for, and what we will and will not promise about getting one.
Roles this prepares you for
AI Security Engineer
Owns the security of AI systems in production: threat modelling, review, and the controls that survive contact with a real deployment.
Product companies, financial services, consultancies
Security Engineer, AI focus
An existing security role extended to cover the AI surface — usually the first person in an organisation asked to assess a model-backed feature.
Enterprises adopting AI internally
Application Security Engineer
Reviews and hardens applications, now including the ones with a model in the request path.
Product and platform teams
Cloud / DevSecOps Engineer
Builds and secures the infrastructure AI systems run on, including the privilege boundaries agents operate within.
Cloud-native organisations, managed service providers
Security Consultant
Assesses client AI deployments and reports findings — a capability few consultancies currently have depth in.
Consultancies, advisory practices
Capabilities you leave with
- AI threat modelling
- Prompt injection defence
- RAG pipeline security
- Model asset classification
- Agent privilege scoping
- AI red teaming
- Incident response
- Security design review
Career support, and what we do not promise
Career support means review, direction and honest feedback — on your CV, on how you describe your work, and on where the gap still is.
What we do and do not promise
We provide industry-relevant skills, practical experience, mentorship, portfolio development and interview readiness. Employment decisions remain with individual employers.
We publish no salary figures, because we have none we can source.
Find out where you stand
Five questions, about a minute. No sign-up, nothing to pay.