DevOps Engineer

This is a fully remote position, open to applicants in New York.

📋 Description

• Analyze intricate infrastructure engineering assignments carried out with cutting-edge AI coding agents.

• Review implementations utilizing cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.

• Evaluate technical accuracy, reliability, maintainability, and operational preparedness.

• Utilize professional engineering judgment in realistic production infrastructure scenarios.

• Integrate frontier AI coding agents into practical infrastructure engineering processes.

• Assess the effectiveness of coding models in interpreting requirements and executing solutions.

• Identify bugs, edge cases, reliability challenges, configuration mistakes, and potential failure modes.

• Determine areas where models need corrections, additional guidance, or manual engineering input.

• Review solutions related to AWS, Azure, GCP, Kubernetes, Terraform, CI/CD, monitoring, logging, alerting, and observability.

• Identify issues concerning security, scalability, resilience, and operational functionality.

• Compare infrastructure solutions generated by various frontier coding models.

• Evaluate implementation strategies, technical reasoning, reliability, and code quality.

• Decide which methods best fulfill task requirements.

• Document model strengths, weaknesses, and recurring patterns of engineering failures.

• Provide concise written assessments that clarify relevant technical trade-offs.

• Complete tasks related to infrastructure implementation reviews, AI coding-agent evaluations, reliability analyses, debugging, and model comparisons.

⛳️ Requirements

• Minimum of 2 years of professional experience in DevOps, Site Reliability Engineering, or Cloud Engineering.

• Practical experience supporting production-scale infrastructure or distributed systems.

• Familiarity with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tools.

• Regularly utilize AI coding agents within technical workflows.

• Strong capability to evaluate model-generated infrastructure and reliability engineering solutions.

• Experience in diagnosing production issues, deployment failures, and infrastructure challenges.

• Excellent technical judgment, debugging abilities, and written communication skills.

• Ability to work effectively within short, intensive project sprints.

• A degree in computer science, software engineering, information technology, cloud computing, or a related technical field may be advantageous.

• Advanced technical training in cloud infrastructure, systems engineering, networking, or DevOps may enhance an application.

• Relevant cloud or infrastructure certifications could also be beneficial.

• Equivalent professional experience in supporting production systems may be considered.

• Experience with AWS, Azure, or Google Cloud Platform.

• Strong background in Kubernetes and container orchestration.

• Proficiency in Terraform or similar infrastructure-as-code tools.

• Experience in designing or maintaining CI/CD pipelines.

• Familiarity with observability platforms, monitoring, logging, and incident response.

• Experience with AI coding tools such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or comparable technologies.

• Knowledge of production reliability, scalability, disaster recovery, and performance engineering.

• Previous experience in AI evaluation, benchmark development, or structured technical reviews is a plus.

🏝️ Benefits

• Fully remote position with flexible scheduling options.

• Sprint-based projects with task durations typically ranging from approximately 12 to 24 hours.

• Compensation of $400 for each accepted task.

• Weekly payments through Stripe or Wise.

• Projects may be extended, shortened, or modified based on scope and performance.

• Opportunity for independent contractor work.

• Engage directly with frontier AI coding agents on realistic infrastructure engineering challenges.

• Participate in intensive technical sprints with compensation based on task completion.