Backend Skills | AI Design Components

📄️ API Patterns

API design and implementation across REST, GraphQL, gRPC, and tRPC patterns

Relational database implementation across Python, Rust, Go, and TypeScript

Vector database implementation for AI/ML applications, semantic search, and RAG systems

Time-series database implementation for metrics, IoT, financial data, and observability

Document database implementation for flexible schema applications

Graph database implementation for relationship-heavy data models

Async communication patterns using message brokers and task queues

Real-time communication patterns for live updates, collaboration, and presence

Monitoring, logging, and tracing with OpenTelemetry

Authentication, authorization, and API security implementation

Data pipelines, feature stores, and embedding generation for AI/ML systems

LLM and ML model deployment for inference

Deployment patterns from Kubernetes to serverless and edge functions

Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources