Design, validate, and deploy robust agentic AI systems that act autonomously while remaining accountable to human oversight. This program equips architects and technical leaders to combine multi-agent patterns, reasoning models, and orchestration frameworks with strong governance. You’ll learn to specify agent roles, tools, and protocols; engineer evaluation harnesses; and operationalize feedback loops that keep agents on-task and aligned with business outcomes.
Cybersecurity is woven into every layer: threat models for tool-use, controls for data leakage, and defenses against prompt and tool-chain attacks. Participants build strategies for secure delegation, auditable actions, and resilient recovery so autonomous behaviors remain trustworthy in adversarial environments. By the end, you can blueprint enterprise-scale agent systems that are observable, controllable, and ready for production.
Learning Objectives:
- Architect multi-agent ecosystems with explicit roles, tools, and guardrails
- Apply ML/NLP/reasoning frameworks to plan, act, and self-reflect
- Design human-in-the-loop oversight with escalation and rollback paths
- Implement safety, transparency, and policy-as-code controls
- Evaluate reliability with offline/online tests, red-teaming, and SLAs
- Embed resilient cybersecurity controls across agent lifecycles
Audience:
- AI/ML Architects and Engineers
- Software and Platform Engineers
- Product and Innovation Leaders
- Data Scientists and MLOps Engineers
- Enterprise and Solutions Architects
- Cybersecurity Professionals
Program Modules:
Module 1: Agentic Foundations
- Agent roles, skills, and tools
- Planning, memory, and reflection loops
- Toolformer, function-calling, adapters
- Orchestration vs. swarms vs. graphs
- Context, state, and grounding
- Capability and risk scoping
Module 2: NLP & Reasoning Models
- LLM selection and system prompts
- Retrieval, grounding, and context windows
- Chain-of-Thought and self-consistency
- Structured outputs and validators
- Domain adapters and fine-tuning options
- Cost, latency, and quality trade-offs
Module 3: Human Oversight Design
- HITL checkpoints and approvals
- Intervention and rollback strategies
- Tiered autonomy and escalation routes
- Action logs and auditability
- UX for reviewing agent plans
- Metrics for supervision load
Module 4: Safety & Control
- Policy-as-code and guardrails
- Tool permissioning and scopes
- Data minimization and redaction
- Jailbreak, prompt-injection defenses
- Rate limits and kill-switch patterns
- Monitoring for drift and misuse
Module 5: Domain Case Studies
- Healthcare intake and coding agents
- Clinical documentation copilots
- Finance underwriting assistants
- Claims and fraud triage agents
- Compliance-aware decision support
- Cross-domain lessons and pitfalls
Module 6: Deployment & Operations
- Reference architectures and CI/CD
- Eval harnesses and canarying
- Observability: traces and events
- Incident response for agents
- Cost governance and quotas
- Roadmaps and incremental rollout
Exam Domains:
- Agentic AI Fundamentals
- Multi-Agent Coordination
- Human-AI Oversight
- Trust and Explainability
- System Safety and Governance
- Compliance and Risk Management
Course Delivery:
The course is delivered through a combination of lectures, interactive discussions, guided workshops, and project-based learning, facilitated by experts in the field of Certified Agentic AI Systems Architect (CAAISA). Participants will have access to online resources, including readings, case studies, and tools for practical exercises.
Assessment and Certification:
Participants will be assessed through quizzes, assignments, and a capstone project. Upon successful completion of the course, participants will receive a certificate in Certified Agentic AI Systems Architect (CAAISA).
Question Types:
- Multiple Choice Questions (MCQs)
- Scenario-based Questions
Passing Criteria:
To pass the Certified Agentic AI Systems Architect (CAAISA) Certification Training exam, candidates must achieve a score of 70% or higher.
Ready to architect trustworthy agentic AI? Enroll now and build secure, auditable autonomous systems with Tonex.