Frontier AI Infrastructure Engineer (Contract)

Mercor

Miami (FL)

On-site

USD 165,000 - 276,000

Full time

14 days+

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Job summary

Mercor partners with a leading AI research lab to support a Frontier Code Agents project focused on evaluating and improving frontier AI coding models within realistic infrastructure engineering workflows.

Contributors assess model-generated infrastructure across cloud platforms, Kubernetes, CI/CD, observability, and automation, spotting bugs and edge cases while applying engineering judgment to practical scenarios.

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 such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
  • Ability to evaluate model-generated infrastructure and reliability engineering solutions.
  • Experience supporting production-scale systems is preferred.

Responsibilities

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

Skills

DevOps experience
SRE experience
Cloud engineering
Kubernetes
Terraform
CI/CD pipelines
Observability tooling
AWS
Azure
GCP
AI coding agents usage

Tools

Cursor
Claude Code
Codex
Windsurf
Gemini CLI

Job description

Mercor partners with a leading AI research lab to support a Frontier Code Agents project focused on evaluating and improving frontier AI coding models within realistic infrastructure engineering workflows.

Contributors assess model-generated infrastructure across cloud platforms, Kubernetes, CI/CD, observability, and automation, spotting bugs and edge cases while applying engineering judgment to practical scenarios.

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