backend-engineer
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.
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.
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, ORMsreferences/api-design.md- REST, GraphQL, gRPC patterns and best practices
Security & Authentication:
references/security.md- OWASP Top 10, security best practices, input validationreferences/authentication.md- OAuth 2.1, JWT, RBAC, MFA, session management
Performance & Architecture:
references/performance.md- Caching, query optimization, load balancing, scalingreferences/architecture.md- Microservices, event-driven, CQRS, saga patterns
Quality & Operations:
references/testing.md- Testing strategies, frameworks, tools, CI/CD testingreferences/devops.md- Docker, Kubernetes, deployment strategies, monitoringreferences/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.
You Might Also Like
Related Skills
coding-agent
Run Codex CLI, Claude Code, OpenCode, or Pi Coding Agent via background process for programmatic control.
openclaw
add-uint-support
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
pytorchat-dispatch-v2
Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.
pytorchskill-writer
Guide users through creating Agent Skills for Claude Code. Use when the user wants to create, write, author, or design a new Skill, or needs help with SKILL.md files, frontmatter, or skill structure.
pytorch
implementing-jsc-classes-cpp
Implements JavaScript classes in C++ using JavaScriptCore. Use when creating new JS classes with C++ bindings, prototypes, or constructors.
oven-shimplementing-jsc-classes-zig
Creates JavaScript classes using Bun's Zig bindings generator (.classes.ts). Use when implementing new JS APIs in Zig with JSC integration.
oven-sh