AI Agent Orchestrator - Multi-Agent System Architecture

Project Overview

The AI Agent Orchestrator is an advanced multi-agent system designed to demonstrate production-grade AI engineering architecture. This system coordinates specialized agents to handle complex diagnostic and analysis tasks through intelligent routing, parallel execution, and context-aware decision making.

Why This Architecture?

This project showcases the design and implementation of scalable AI systems. Rather than a single monolithic AI, the orchestrator routes tasks to specialized agents optimized for specific domains (network diagnostics, log analysis, system monitoring), demonstrating how to build production AI systems that scale and maintain expertise across different areas.

Technology Stack

Python FastAPI LangChain AWS Lambda AWS Bedrock / OpenAI API Gateway DynamoDB Multi-Agent Systems

System Architecture

The orchestrator follows a secure, serverless architecture pattern with proxy-based API security:

Frontend Layer
Portfolio Chatbot (js/modules/chatbot.js)
Auto-detect + Manual Mode Switching

↓ HTTPS Request

API Gateway
Existing Portfolio API

↓ Routes to...

Chatbot Lambda (Node.js)
lambda/chatbot-handler/index.js
- Detects Orchestrator Keywords
- IT Support Mode → RAG + Bedrock
- Orchestrator Mode → Lambda.invoke()

↓ Lambda-to-Lambda Invocation

Orchestrator Lambda (Python)
lambda/orchestrator-lambda/
- Task Analysis
- Agent Selection (Network, Logs, System, Code, Docs)
- Intelligent Routing

↓ AI Processing

AWS Bedrock
Claude 3 Haiku (Cost-Efficient)
~$0.002/request

All-Lambda Architecture Benefits

Cost-Efficient: ~$2/month total (vs. $8-10/month for EC2)
Low Latency: Direct Lambda-to-Lambda invocation
Secure: IAM-based permissions, no API keys needed
Scalable: Automatic scaling with AWS Lambda
Zero Maintenance: No servers to manage

Specialized Agents

Each agent is optimized for specific diagnostic domains with custom tools and expertise:

Network Agent

Network diagnostics, connectivity analysis, DNS resolution, latency testing

In Development

Log Analysis Agent

Parse system and application logs, error detection, pattern analysis

Planned

System Monitor Agent

System health checks, performance metrics, resource utilization analysis

Planned

Code Analysis Agent

Code review, security scanning, best practice recommendations

Planned

Documentation Agent

Generate API docs, README files, inline code documentation

Planned

Key Features

Intelligent Routing: Analyzes tasks and selects the most appropriate agent(s) for execution
Parallel Execution: Coordinates multiple agents working simultaneously on complex tasks
Context Awareness: Maintains conversation context and learns from previous interactions
Secure API Design: Proxy pattern protects API keys and implements rate limiting
Serverless Architecture: AWS Lambda deployment for cost-effective scaling
Extensible Framework: Easy to add new agents with custom capabilities

Technical Highlights

Multi-Agent Orchestration

The orchestrator uses advanced routing logic to determine the best agent(s) for each task:

Natural language task analysis using LLM-based classification
Dynamic agent selection based on capabilities and current system state
Sequential and parallel execution strategies
Agent handoff protocols for complex multi-stage tasks

Security Architecture

Following production best practices with defense-in-depth approach:

API keys stored in AWS Lambda environment variables (never client-side)
Request validation and sanitization at proxy layer
Rate limiting per client to prevent abuse
CloudWatch logging for monitoring and debugging
CORS configuration restricted to portfolio domain

Scalability & Cost

Serverless architecture enables efficient scaling and cost optimization:

Pay-per-request pricing (~$1-5/month expected usage)
Automatic scaling with AWS Lambda
DynamoDB for cost-effective state storage
Async processing for long-running tasks

Live Demo

The orchestrator API is currently under development. The backend Lambda functions are being implemented and will be deployed soon. Check back to try the live demo!

Demo Coming Soon

View source code and architecture documentation on GitHub

Implementation Roadmap

Phase 1 (Current): Core orchestrator framework and Network Agent implementation
Phase 2: AWS Lambda deployment with API Gateway integration
Phase 3: Additional agent implementations (Logs, System, Code)
Phase 4: Advanced features (parallel execution, context memory, learning)

Skills Demonstrated

System Architecture: Multi-tier serverless design, API security patterns, microservices architecture
AI Engineering: Multi-agent coordination, LangChain integration, prompt engineering
Backend Development: FastAPI, Python async, RESTful API design
Cloud Platform: AWS Lambda, API Gateway, DynamoDB, CloudWatch
Security: API key management, rate limiting, input validation

View on GitHub