Devops Engineer - Ai Model Evaluator

Mercor; San Francisco (CA); Hybrid; GBP 74,000 - 101,000; Part time

Job summary

Mercor is hiring a DevOps/SRE/Cloud Engineer (Coding Agent Experience) to work remotely on frontier AI coding agents for infrastructure tasks. The role covers evaluating model-generated infrastructure, cloud platforms, Kubernetes, CI/CD, observability, and automation.

Candidates should have 2+ years in DevOps/SRE/Cloud Eng and hands-on cloud and tooling experience. As a contractor, you will collaborate asynchronously to meet sprint goals, with compensation tied to accepted tasks and performance.

Qualifications

• 2+ years of professional DevOps/SRE/Cloud Engineering experience.
• Experience with AWS/Azure/GCP and Kubernetes/.Terraform or CI/CD pipelines or observability tooling.

Responsibilities

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

Skills

DevOps/SRE/Cloud Eng

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD

Observability

AI coding agents

Model evaluation

Tools

Kubernetes tooling

CI/CD tooling

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.
• Compare outputs from multiple frontier models and assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.
• Work independently and asynchronously to meet sprint-based project deadlines.

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 is tied to accepted work.

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