Cloud Engineer - Fully Remote | Upto $85/hr

mercor; San Francisco (CA); Hybrid; CAD 141,000 - 192,000; Part time

Job summary

Mercor is seeking a remote Contract DevOps/SRE/Cloud Engineer to collaborate with leading AI research teams. You will leverage frontier AI coding agents to perform and assess complex infrastructure tasks across cloud platforms and automation tooling.

The role emphasizes reliability, edge-case analysis, and rigorous evaluation of model-generated solutions.

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.

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 , 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.

Skills

DevOps/SRE

AI tooling

Cloud platforms

Kubernetes

CI/CD

Model evaluation

Tools

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD pipelines

Observability tooling

Job description

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .

Position

DevOps / SRE / Cloud Engineer (Coding Agent Experience)

Type

Contract

Compensation

$85/hour

Location

Remote

Role 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 , 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.

Qualifications Must-Have

• 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.

Preferred

• Experience supporting production-scale systems.

Compensation & Legal

$400 per accepted task

Compensation tied to accepted work.

Application Process (Takes 20–30 mins to complete)

• Upload resume
• AI interview based on your resume
• Submit form

Resources & Support

• For details about the interview process and platform information, please check:
• For any help or support, reach out to:

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.