Remote | DevOps Engineer — $50–$100/hour

engineeringjobs.net, Inc.; New York (NY); Remote; USD 69,000 - 138,000; Full time

Job summary

24-MAG LLC is seeking experienced DevOps, SRE, Platform, and Infrastructure Engineers to contribute to an advanced AI training and technical evaluation project. Candidates should have hands-on cloud infra, Kubernetes, Terraform, CI/CD, Python, Linux, and IaC skills to design realistic tasks and reference solutions.

Selected contractors will craft production-style scenarios, build reproducible references, and deliver precise AI-output evaluations with thorough corrections, ensuring correctness

Qualifications

• 3 years of professional DevOps/SRE/Platform experience.
• Strong coding ability in Python, Go, Bash or TypeScript.
• Hands-on experience with CI/CD systems (GitHub Actions, GitLab CI, Jenkins).
• Expertise with Docker and Kubernetes.
• Experience with Terraform, Ansible, Pulumi, CloudFormation, or similar IaC tools.
• Experience with at least one major cloud platform (AWS, GCP, or Azure).
• Advanced Linux and Git proficiency.
• Excellent written and spoken English.

Responsibilities

• Design production-style DevOps tasks and evaluation scenarios.
• Create reference solutions with setup, execution, and validation steps.
• Review AI-generated outputs and write precise corrective feedback.
• Assess scalability, reliability, and security of infrastructure tasks.
• Document assumptions, dependencies, and environment requirements.
• Ensure reproducibility and clear evaluation criteria.

Skills

Python

Go

Bash

TypeScript

Tools

Docker

Kubernetes

Terraform

Ansible

Pulumi

CloudFormation

GitHub Actions

GitLab CI

Jenkins

Job description

We are sharing a specialised consulting opportunity for experienced DevOps, SRE, Platform, and Infrastructure Engineers with strong expertise in Kubernetes, Terraform, CI/CD, Python, Linux, cloud infrastructure, and infrastructure as code to contribute to an advanced AI training and technical evaluation project.

Selected professionals will design realistic DevOps tasks based on production-style scenarios, build working reference solutions, evaluate AI-generated technical outputs, and provide precise corrections grounded in practical infrastructure engineering. The work requires strong coding ability, hands-on cloud and platform experience, and a high standard for correctness and reproducibility. No prior experience in AI is required.

Key Responsibilities

DevOps Scenario & Task Design

• Design realistic technical tasks based on production-style DevOps environments
• Create scenarios involving CI/CD, containers, orchestration, infrastructure as code, monitoring, and incident response
• Ensure tasks reflect practical engineering constraints rather than purely theoretical exercises
• Define clear expected outcomes and validation criteria
• Maintain technical realism across infrastructure and platform-engineering workflows

Reference Solutions & Reproducibility

• Write working reference solutions for DevOps and infrastructure tasks
• Provide clear setup, execution, and validation steps
• Build reproducible solutions that can be verified consistently
• Document assumptions, dependencies, and environment requirements
• Maintain a strict quality bar for technical correctness

AI Output Review & Technical Evaluation

• Review AI-generated solutions to DevOps and infrastructure problems
• Identify technical failures, incorrect assumptions, and incomplete implementations
• Write precise corrections explaining both the issue and the appropriate solution
• Evaluate outputs for correctness, reliability, and operational viability
• Provide structured feedback that improves future task and evaluation quality

Cloud, Containers & Infrastructure as Code

• Work with Docker, Kubernetes, and modern containerised infrastructure
• Design or evaluate CI/CD workflows using platforms such as GitHub Actions, GitLab CI, or Jenkins
• Apply Infrastructure as Code using Terraform, Ansible, Pulumi, CloudFormation, or comparable tools
• Work across at least one major cloud platform such as AWS, GCP, or Azure
• Apply strong Linux and Git practices across technical workflows

Platform Reliability & Engineering Quality

• Assess infrastructure solutions for scalability, reliability, maintainability, and security
• Diagnose deployment, configuration, or automation failures
• Incorporate observability and operational best practices where relevant
• Maintain consistent standards across production-style engineering tasks
• Contribute structured feedback that supports continuous improvement of technical evaluation frameworks

Ideal Profile

• 3 years of professional experience in DevOps, SRE, Platform Engineering, Infrastructure Engineering, or a closely related role
• Strong coding ability in Python, Go, Bash, TypeScript, or comparable languages
• Ability to work with real application and infrastructure code rather than relying solely on basic scripting
• Practical experience with CI/CD systems such as GitHub Actions, GitLab CI, or Jenkins
• Strong experience with Docker and Kubernetes
• Hands-on experience with at least one major cloud platform, including AWS, GCP, or Azure
• Infrastructure as Code experience with Terraform, Ansible, Pulumi, CloudFormation, or comparable tooling
• Advanced Linux and Git proficiency
• Strong written and spoken English
• Experience with observability platforms such as Prometheus, Grafana, Datadog, or OpenTelemetry is advantageous
• Security, secrets-management, or platform-reliability experience is beneficial
• Open-source contributions or technical-writing experience are valued
• Previous AI-training or model-evaluation experience is beneficial but not required
• No prior experience in AI is required

Engagement Details

• Independent contractor engagement
• Fully remote
• Compensation: $50--$100/hour
• Minimum availability: approximately 20 hours per week
• Work will involve DevOps task design, reference-solution development, AI-output evaluation, cloud infrastructure, CI/CD, containers, and Infrastructure as Code
• Strong coding ability and hands-on infrastructure experience are central to this engagement
• Assignments may involve Kubernetes, Terraform, Linux, Git, Docker, cloud platforms, monitoring, and incident-response scenarios
• Project scope, workload, technical focus, and evaluation standards may evolve depending on project requirements
• Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.