Data Annotation is seeking DevOps Engineers to evaluate how AI models handle CI/CD, infrastructure-as-code, containers, and cloud operations. The role involves identifying failures in model automation—such as insecure defaults or broken state files—and writing correct solutions that a platform engineer would trust.
- Compensation ranges from $75 to over $150 per hour based on difficulty.
- No degree is required for the position; hands-on experience with tools like Terraform, Kubernetes, or Docker is prioritized.
- The role offers flexible hours as an independent contractor working remotely.
- Compensation ranges from $75 to over $150 per hour based on difficulty.
- No degree is required for the position; hands-on experience with tools like Terraform, Kubernetes, or Docker is prioritized.
- The role offers flexible hours as an independent contractor working remotely.
Over 160 production-ready skill documents (SKILL.md) for LLM coding agents like Claude Code, Cursor, and Codex.Each skill contains expert-level configs, CLI commands, troubleshooting guides, and ready-to-run scripts spanning six domains: DevOps (CI/CD, Kubernetes, observability), Security (vulnerability scanning, secrets, hardening), Infrastructure (AWS/Azure/GCP, networking, databases, local inference stacks), LLM engineering (agent evals, RAG infrastructure, inference scaling), Compliance (SOC2, HIPAA, GDPR, ISO 27001), and IT operations. Skills install in under a minute via the `npx skills add` CLI or a simple git clone, and the agent discovers, matches, and activates them on demand.
- Ships with notable niche skills absent from other repos: MCP server security, eBPF kernel-level observability, OpenTofu migration, agent-eval CI/CD gates, and multi-tenant LLM hosting with KEDA autoscaling.
- Ships with notable niche skills absent from other repos: MCP server security, eBPF kernel-level observability, OpenTofu migration, agent-eval CI/CD gates, and multi-tenant LLM hosting with KEDA autoscaling.
Platform Engineering Labs has released formae, an open-source infrastructure-as-code platform designed to address limitations in existing tools, focusing on automatic discovery, codification of existing infrastructure, and a reconcile/patch workflow. It uses PKL instead of HCL and targets reducing drift and complexity.
AIaC is an Artificial Intelligence Infrastructure-as-Code Generator, providing community support and tools to streamline AI infrastructure setup.
