Remote Cloud Engineer - AI-Driven DevOps/SRE

mercor; Denmark; A distancia; DKK 735.000 - 873.000; Jornada completa

Descripción de la vacante

Mercor is seeking a DevOps / SRE / Cloud Engineer (Coding Agent Experience) for remote engagement. You will use frontier AI coding agents to complete and evaluate complex infrastructure tasks, review model-generated implementations across cloud platforms, Kubernetes, CI/CD, observability, and automation.

You will identify bugs and reliability issues in model outputs, compare multiple frontier models, and apply professional engineering judgment to realistic infrastructure scenarios.

Formación

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

Responsabilidades

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

Conocimientos

2+ years devops/sre/cloud

AI coding agents experience

model evaluation

Herramientas

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD

Observability tooling

Descripción del empleo

Mercor is seeking a DevOps / SRE / Cloud Engineer (Coding Agent Experience) for remote engagement. You will use frontier AI coding agents to complete and evaluate complex infrastructure tasks, review model-generated implementations across cloud platforms, Kubernetes, CI/CD, observability, and automation.

You will identify bugs and reliability issues in model outputs, compare multiple frontier models, and apply professional engineering judgment to realistic infrastructure scenarios.