skills.rest
ColbyRReichenbach
ColbyRReichenbachCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

backend_engineer

Develop FastAPI backend APIs with Stripe and Shopify webhook integrations.

Updated Aug 23, 2026
Search Tags:#authentication#backend#FastAPI#rate-limiting#webhooks#celery
One-click install
npx skills add https://github.com/ColbyRReichenbach/retentionAI --skill backend-engineer-colbyrreichenbach
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: backend_engineer
Source: https://github.com/ColbyRReichenbach/retentionAI/tree/main/.claude/skills/backend_engineer
Command: npx skills add https://github.com/ColbyRReichenbach/retentionAI --skill backend-engineer-colbyrreichenbach

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Backend API development for retentionAI, enabling scalable FastAPI endpoints, webhook integrations, and reliable asynchronous tasks to drive automated customer retention workflows.

Core Features & Use Cases

  • FastAPI project structure: Clear organization of endpoints, services, models, and tasks for maintainable code.
  • Webhook handling: Stripe/Shopify integration with signature verification and idempotent processing.
  • Decision routing & business logic: Orchestrates CLV, uplift, and campaigns.
  • Celery tasks & async processing: Offload long-running jobs like email sending and model retraining.
  • Security & reliability: API authentication, rate limiting, error handling, and retries.
  • Use Case: Build a backend that processes Stripe webhooks, routes decisions, and queues campaigns with reliable retries.

Quick Start

Create a minimal FastAPI app demonstrating webhook handling, a DecisionRouter service, and a sample endpoint to show orchestration.

Frequently Asked Questions about backend_engineer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I structure a FastAPI project for backend APIs and webhook integrations?▼

A FastAPI backend project structure separates endpoints, services, models, and tasks to maintain clean code. This organization supports scalable webhook integrations and reliable asynchronous processing for production-grade services.

How do I handle Stripe and Shopify webhooks in a FastAPI application?▼

Handling Stripe and Shopify webhooks requires signature verification and idempotent processing to ensure reliability. A FastAPI backend can orchestrate these integrations while routing business logic and queuing subsequent campaigns.

What is the best way to manage asynchronous tasks and long-running jobs in a FastAPI backend?▼

Managing asynchronous tasks in a FastAPI backend is best handled using Celery. It offloads long-running jobs like email sending and model retraining, ensuring the API remains responsive while executing background processing.

Can I use Celery with FastAPI for automated customer retention workflows?▼

Yes, Celery integrates with FastAPI to drive automated customer retention workflows. This combination enables reliable decision routing, campaign queuing, and robust retry mechanisms for long-running asynchronous jobs.

How do you implement rate limiting and authentication for backend APIs?▼

Implementing rate limiting and authentication for backend APIs requires deterministic security checks within the service layer. This ensures structured access control and protects production-grade endpoints from excessive requests.

Why do my webhook integrations fail under high volume in production?▼

Webhook integrations fail under high volume without robust error handling, idempotent processing, and retry mechanisms. Implementing structured service layers and rate limiting ensures reliable webhook processing at scale.

Related Skills

Explore More Software Engineering Skills→
eliascoelho911eliascoelho911

fastapi-templates

Create FastAPI applications with async patterns and structured project templates.

Community
Advanced
GaneshMadarasuGaneshMadarasu

retraining-worker

Analyze Kafka-triggered model retraining workflows with Celery and Redis.

Community
Advanced
FortiumPartnersFortiumPartners

using-celery

Implement distributed task queues and periodic scheduling for Python with Celery.

Official
Advanced
imehrimehr

python-backend-guidelines

Optimize Python backend structure with layered patterns for FastAPI, Django, and Flask.

Community
Basic