AI-Enabled DevOps Engineer: Cloud, Kubernetes & CI/CD

OpenTalent; United States; On-site; USD 4,500 - 5,600; Full time

Benefits offered by this job

Task-based compensation

Job summary

OpenTalent seeks an experienced DevOps/Cloud Engineer to work with frontier AI coding agents on complex infrastructure tasks. You will review model-generated implementations across AWS, Azure, GCP, Kubernetes, and automation tooling, ensuring reliability and correctness.

Strong judgment is essential for realistic infrastructure scenarios. The role emphasizes evaluating diverse model outputs, identifying edge cases and bugs, and refining approaches based on rigorous analysis.

Qualifications

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling.
• Regular use of AI coding agents like Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.

Responsibilities

• Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
• Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, and infrastructure automation.
• Identify bugs, edge cases, reliability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models to assess strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.

Skills

DevOps / SRE experience

Cloud engineering

AI coding tools experience

Model evaluation of infra outputs

Tools

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD

Observability tooling

Job description

OpenTalent seeks an experienced DevOps/Cloud Engineer to work with frontier AI coding agents on complex infrastructure tasks. You will review model-generated implementations across AWS, Azure, GCP, Kubernetes, and automation tooling, ensuring reliability and correctness.

Strong judgment is essential for realistic infrastructure scenarios. The role emphasizes evaluating diverse model outputs, identifying edge cases and bugs, and refining approaches based on rigorous analysis.