DevOps Engineer

Job not on LinkedIn

🔥 0 minutes ago

🗽 New York – Remote

🗽 New York – Remote

💵 $80 / hour

⏳ Contract/Temporary

🟢 Junior

🟡 Mid-level

⛑ DevOps & Site Reliability Engineer (SRE)

🚫👨‍🎓 No degree required

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24-MAG

WebsiteLinkedInAll Job Openings

2 - 10 employees

🤝 B2B

💼 Consulting

B2B • Consulting

24-MAG is a commercial strategy and execution firm that helps B2B organizations design and implement systems, workflows, and operating rhythms for sales, client management, and cross-functional projects. They focus on transforming scattered processes into aligned, measurable, and scalable commercial functions—covering pipeline structure, account management frameworks, and operational discipline for teams seeking efficient, intentional growth.

📋 Description

• 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 • Review AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, logging, alerting, and observability solutions • Identify security, scalability, resilience, and operational concerns • Compare infrastructure solutions produced by multiple frontier coding models • Assess 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 • Complete infrastructure implementation review, AI coding-agent evaluation, reliability analysis, debugging, and model comparison tasks

🎯 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 • A degree in computer science, software engineering, information technology, cloud computing, or a related technical discipline may be helpful • Advanced technical training in cloud infrastructure, systems engineering, networking, or DevOps may strengthen an application • Relevant cloud or infrastructure certifications may also be valuable • Equivalent professional experience supporting production systems may be considered • 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

🏖️ Benefits

• Fully remote with flexible scheduling • Sprint-based project with task windows typically spanning approximately 12–24 hours • Compensation of $400 per accepted task • Weekly payments via Stripe or Wise • Projects may be extended, shortened, or adjusted depending on scope and performance • Independent contractor opportunity • Work directly with frontier AI coding agents on realistic infrastructure engineering problems • Participate in intensive technical sprints with task-based compensation