Jnachi Certified Agentic AI & Multi-Agent Systems Engineer
Validates elite architectural competence in designing, testing, and deploying autonomous AI agent systems. Assesses ReAct/Plan-and-Solve cognitive loops, LangGraph state graphs, hierarchical multi-agent delegation, Model Context Protocol (MCP) integrations, human-in-the-loop governance, and resilience against infinite loops.
Jnachi Certified Agentic AI & Multi-Agent Systems Engineer
Validates architectural and implementation mastery in designing, orchestrating, and securing autonomous AI agent systems using LangGraph, CrewAI, AutoGen, and Model Context Protocol (MCP).
Exam Competency Matrix & Domain Breakdown
Select any domain below to inspect tested skills, real-world scenarios, and preparation materials.
Agentic Paradigms, ReAct Loops & Cognitive Architectures
ReAct cognitive loops, Plan-and-Solve strategies, LLM reasoning patterns, autonomous goal decomposition, and deterministic stop conditions.
Thought-Action-Observation loops, scratchpad memory management, dynamic tool invocation, error correction, and loop breakout mechanisms.
JSON Schema definition for tools, deterministic argument extraction, handling malformed tool responses, and structured outputs.
Portal Registration Required Before Exam
Your full name, location, and organization are verified and printed directly on your official diploma.
Exam Objectives & Tested Competencies
ReAct, Plan-and-Solve Loops & Cognitive Architectures
Evaluated in scenario-based proctored questions.
LangGraph State Graphs, Memory & Checkpointing
Evaluated in scenario-based proctored questions.
Hierarchical Multi-Agent Orchestration & Tool Routing
Evaluated in scenario-based proctored questions.
Model Context Protocol (MCP), Guardrails & Safety Hooks
Evaluated in scenario-based proctored questions.
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