Remote | DevOps Engineer — Up to $80/hour

24-MAG is seeking experienced DevOps, Site Reliability, and Cloud Engineering professionals for a part-time consulting opportunity. The role involves evaluating infrastructure engineering tasks completed with AI coding agents, assessing implementations, and providing technical judgment on model-generated solutions.

Responsibilities:

• Review complex infrastructure engineering tasks completed with frontier AI coding agents
• Evaluate implementations involving cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation
• Assess technical correctness, reliability, maintainability, and operational readiness
• Apply professional engineering judgment to realistic production infrastructure scenarios
• Use frontier AI coding agents within practical infrastructure engineering workflows
• Evaluate how effectively coding models interpret requirements and implement solutions
• Identify bugs, edge cases, reliability issues, configuration errors, and failure modes
• Assess where models require correction, additional prompting, or manual engineering intervention
• Evaluate solutions involving AWS, Azure, GCP, or comparable cloud environments
• Review Kubernetes configurations, deployment workflows, and infrastructure orchestration
• Assess Terraform or similar infrastructure-as-code implementations
• Review CI/CD pipelines, monitoring, logging, alerting, and observability approaches
• Identify security, scalability, resilience, and operational concerns where relevant
• Compare infrastructure solutions produced by multiple frontier coding models
• Assess differences in implementation strategy, technical reasoning, reliability, and code quality
• Determine which approaches best satisfy task requirements
• Document model strengths, weaknesses, and recurring engineering failure patterns
• Provide clear written assessments explaining relevant technical trade-offs

Requirements:

• At least 2 years of professional DevOps, Site Reliability Engineering, or Cloud Engineering experience
• Hands-on experience supporting production-scale infrastructure or distributed systems
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling
• Regular use of AI coding agents within technical workflows
• Strong ability to evaluate model-generated infrastructure and reliability engineering solutions
• Experience diagnosing production issues, deployment failures, and infrastructure problems
• Strong technical judgment, debugging skills, and written communication
• Ability to work efficiently within short, intensive project sprints
• Experience with AWS, Azure, or Google Cloud Platform
• Strong Kubernetes and container orchestration experience
• Expertise with Terraform or comparable infrastructure-as-code tooling
• Background designing or maintaining CI/CD pipelines
• Familiarity with observability platforms, monitoring, logging, and incident response
• Experience with Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable AI coding tools
• Knowledge of production reliability, scalability, disaster recovery, and performance engineering
• Previous exposure to AI evaluation, benchmark development, or structured technical review