Certified AI Agent Systems Architect
Demonstrate verified mastery of production agent architectures, Model Context Protocol integration, durable Human-in-the-Loop workflows, and defense-in-depth safety engineering.
🌳 Systems Architect Skill Tree
Four core competency pillars required for enterprise AI agent systems certification.
Foundations & Control Flow
ReAct reasoning loops, DAG task decomposition, supervisor-worker hierarchies, and cycle-depth bounds.
- ✓ LangGraph State Graphs
- ✓ Dynamic DAG Replanning
- ✓ Budget Circuit Breakers
Protocols & Tooling
Model Context Protocol (MCP), Agent-to-Agent (A2A), JSON-RPC 2.0 stdio/SSE, and Pydantic validation.
- ✓ MCP Client / Server Spec
- ✓ Strict JSON Schema Bounds
- ✓ Tool Handshake Negotiation
Durable State & HITL
Zero-compute execution pauses, PostgreSQL frame serialization, webhook hydration, and microVM sandboxes.
- ✓ Stateless Worker Pools
- ✓ Firecracker Jail Boundaries
- ✓ Webhook Resume Hydration
Safety & Cost Scaling
Dual-LLM privilege separation, indirect prompt injection defense, prompt context caching, and OpenTelemetry.
- ✓ Dual-LLM Air-Gap DMZ
- ✓ Context Caching (90% savings)
- ✓ Hallucination Attributions
Systems Architect Capstone Exam
10 production scenario questions. Select the correct architectural decision for each problem.
Your Official Verified Credential
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Certified AI Agent Systems Architect
This is to certify that
has successfully passed the comprehensive Technical Capstone Examination covering Hierarchical Multi-Agent Topologies, Model Context Protocol (MCP) tool integration, Durable Checkpoint State Machines, MicroVM Sandboxing, and Dual-LLM Privilege Separation.