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Agentic AIadvanced

LLM Agents into E-Commerce Systems - FDE ROLE

Modernize an existing e-commerce monolith by building and integrating an AI-powered conversational shopping assistant using Pydantic AI and Groq. Take an enterprise codebase through discovery, standalone proof-of-concept development with safety guardrails, and full production integration. Deploy the unified FastAPI application on Google Cloud Run with comprehensive evaluations, Logfire observability, and automated CI/CD pipelines.

29 lectures

What You Will Learn

Mastering the Forward-Deployed AI Engineer workflow across legacy discovery, isolated POC, and production integration
Building conversational AI agents with Pydantic AI and MongoDb
Implementing dual-layer safety guardrails
Evaluating LLM system performance
Instrumenting production observability with Pydantic Logfire
Deploying containerized AI monoliths to Google Cloud Run

System Architecture

LLM Agents into E-Commerce Systems - FDE ROLE Architecture Diagram

High-level architecture overview of the LLM Agents into E-Commerce Systems - FDE ROLE .

What You'll Build

  • Isolated Pydantic AI shopping assistant POC featuring natural language product search tools
  • Dual-model safety guardrail pipeline screening incoming queries and outgoing assistant responses
  • Offline and live LLM evaluation suite validating tool selection and response accuracy
  • Containerized production FastAPI monolith deployed on Google Cloud Run with automated secret resolution

Project Instructor

Divesh Jadhwani

Divesh Jadhwani

3+ years exp
LinkedIn
LLM Agents into E-Commerce Systems - FDE ROLE
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