Secure Implementation of AI Agents
The only subsidised training that teaches you to build AI agents with security-by-design. From architecture to production deployment, with no shortcuts on security.
The context
90% of AI agent pilots fail. Most due to security and governance issues.
Building an AI agent that works in a demo is easy. Building one that works in production without leaking data, without executing unauthorised actions and without creating legal liabilities is another matter. This course covers exactly that.
Programme
Programme content
AI agent architectures
- Design patterns: ReAct, Plan-and-Execute, Multi-Agent
- Agent orchestration: frameworks and comparison (LangChain, CrewAI, Autogen)
- Tool design (Tool-Use): APIs, databases, internal services
- State management, memory and context in long-running agents
Integration with APIs and enterprise systems
- Secure connection to internal and external APIs
- Authentication, authorisation and principle of least privilege
- Sensitive data handling: PII, financial data, health data
- Integration patterns with ERPs, CRMs and legacy systems
Applied security for AI agents
- Threat modelling for agents: specific attack surfaces
- Sandboxing: execution isolation and permission control
- Guardrails: input validation, output filtering, action limits
- Prompt injection, data poisoning and jailbreaking: attacks and defences
- Logging and auditing: complete traceability of agent decisions
Testing and AI agent quality
- Agent testing: unit, integration, end-to-end
- Response quality evaluation (LLM-as-judge, metrics)
- Security testing: fuzzing, adversarial testing, red teaming
- Production monitoring: alerts, drift detection, degradation
Production deployment
- Infrastructure: containers, serverless, edge
- CI/CD for AI agents: secure deployment pipelines
- Scalability: cost management, rate limiting, caching
- Rollback and circuit breakers: what to do when the agent fails
- Regulatory compliance: technical documentation for EU AI Act
Outcomes
What you will achieve
You can design and implement AI agents with secure architectures from the start
You master integration with APIs and enterprise systems without exposing sensitive data
You can apply guardrails, sandboxing and monitoring to any agent in production
You have a testing and deployment pipeline ready for real production environments
Who it is for
- Developers and technical teams building AI agents
- Software architects designing systems with AI components
- DevOps/MLOps needing to deploy agents in production
- CTOs and tech leads overseeing technical implementation
Who it is NOT for
- Executives without technical background (see AI Agent Use Cases for Business)
- Teams needing a basic AI introduction (see Secure AI Foundations)
- Compliance profiles without technical background (see EU AI Act: Practical Compliance)
Methodology
Format and methodology
100% online, at your pace
30 hours of structured content. Each 6-hour module designed to be completed in one week.
Hands-on labs
Each module includes labs where you build, attack and secure real agents. Not just theory.
Source code included
Repository with working examples, guardrail templates and CI/CD pipelines ready to adapt.
Accreditable certificate
Completion certificate with competency details. Valid for FUNDAE.
Investment and FUNDAE
Investment
This training is subsidisable through FUNDAE. 30 hours of advanced technical training.
* Depends on your company's available FUNDAE credit. We calculate it for you at no obligation.
"I thought it would be too basic for my technical team and too dense for the rest. I was wrong on both counts. We were implementing the AI agents module in production three weeks later."
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