backend-engineer

name	backend-engineer
description	Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
license	MIT
version	1.0.0

Backend Engineer

Production-ready backend development with modern technologies, best practices, and proven patterns.

When to Use

• Designing RESTful, GraphQL, or gRPC APIs
• Building authentication/authorization systems
• Optimizing database queries and schemas
• Implementing caching and performance optimization
• OWASP Top 10 security mitigation
• Designing scalable microservices
• Testing strategies (unit, integration, E2E)
• CI/CD pipelines and deployment
• Monitoring and debugging production systems

Technology Selection Guide

Languages: Node.js/TypeScript (full-stack), Python (data/ML), Go (concurrency), Rust (performance) Frameworks: NestJS, FastAPI, Django, Express, Gin Databases: PostgreSQL (ACID), MongoDB (flexible schema), Redis (caching) APIs: REST (simple), GraphQL (flexible), gRPC (performance)

See: references/technologies.md for detailed comparisons

Reference Navigation

Core Technologies:

• references/technologies.md - Languages, frameworks, databases, message queues, ORMs
• references/api-design.md - REST, GraphQL, gRPC patterns and best practices

Security & Authentication:

• references/security.md - OWASP Top 10, security best practices, input validation
• references/authentication.md - OAuth 2.1, JWT, RBAC, MFA, session management

Performance & Architecture:

• references/performance.md - Caching, query optimization, load balancing, scaling
• references/architecture.md - Microservices, event-driven, CQRS, saga patterns

Quality & Operations:

• references/testing.md - Testing strategies, frameworks, tools, CI/CD testing
• references/devops.md - Docker, Kubernetes, deployment strategies, monitoring
• references/implementation-workflow.md - Unified implementation workflow

Key Best Practices

Security: Argon2id passwords, parameterized queries, OAuth 2.1 + PKCE, rate limiting, security headers

Performance: Redis caching (90% DB load reduction), database indexing, CDN, connection pooling

Testing: 70-20-10 pyramid (unit-integration-E2E), contract testing for microservices

DevOps: Blue-green/canary deployments, feature flags, Kubernetes, Prometheus/Grafana monitoring, OpenTelemetry tracing

Quick Decision Matrix

Need	Choose
Fast development	Node.js + NestJS
Data/ML integration	Python + FastAPI
High concurrency	Go + Gin
Max performance	Rust + Axum
ACID transactions	PostgreSQL
Flexible schema	MongoDB
Caching	Redis
Internal services	gRPC
Public APIs	GraphQL/REST
Real-time events	Kafka

Implementation Checklist

API: Choose style → Design schema → Validate input → Add auth → Rate limiting → Documentation → Error handling

Database: Choose DB → Design schema → Create indexes → Connection pooling → Migration strategy → Backup/restore → Test performance

Security: OWASP Top 10 → Parameterized queries → OAuth 2.1 + JWT → Security headers → Rate limiting → Input validation → Argon2id passwords

Testing: Unit 70% → Integration 20% → E2E 10% → Load tests → Migration tests → Contract tests (microservices)

Deployment: Docker → CI/CD → Blue-green/canary → Feature flags → Monitoring → Logging → Health checks

Implementation Workflow

When implementing backend code, follow unified implementation workflow patterns. See references/implementation-workflow.md for details.