Cloud DevOps Infrastructure AI Training Engineer

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role and the #1 platform for finding and building careers in AI training and data labeling. OpenTrain helps people discover specialized projects, build an AI training profile, and apply in minutes.

Creating an OpenTrain account is free. In this contract role, your cloud and DevOps expertise will help shape how advanced AI systems understand infrastructure engineering.

About AI Training Work

AI training is the human side of building modern artificial intelligence. Experts create examples, assess model-generated work, and write clear feedback that helps AI systems produce more accurate and useful results.

For technical specialists, this can include designing difficult engineering scenarios, reviewing proposed solutions, and building evaluation standards for subjects such as Kubernetes operations, cloud architecture, and infrastructure automation.

• Contribute to the development of cutting-edge generative AI systems
• Apply practical engineering knowledge to realistic technical evaluation tasks
• Work in a fast-growing field where human judgment directly influences AI quality

The Role

OpenTrain AI is seeking a Cloud and DevOps Infrastructure AI Training Engineer for a team developing foundational large language models. You will influence the quality of AI training and inference infrastructure data by designing tasks, evaluating solutions, and developing frameworks for cloud and Kubernetes engineering topics.

This is a US contractor and part-time opportunity with compensation of $75 to $110 per hour. The role listing indicates availability of 20 or more hours per week, while the role requirements call for reliable engagement of at least 40 hours per week during weekdays.

• Location: United States
• Language: English
• Engagement: Contractor, part-time
• Pay: $75 to $110 per hour
• Data focus: Text generation and evaluation rating

What You'll Do

You will work as a technical subject-matter expert, turning real cloud infrastructure and DevOps reasoning into high-quality training and evaluation material. Your work will combine task design, solution writing, technical review, and rubric development.

You will also collaborate with other subject-matter experts to keep training data accurate and consistent across complex infrastructure scenarios.

• Guide research and engineering teams in closing knowledge gaps related to cloud infrastructure, Kubernetes operations, and Infrastructure-as-Code
• Design challenging, domain-relevant tasks involving cluster diagnosis, AWS service integration, and infrastructure automation
• Write accurate, well-structured solutions to technical infrastructure problems
• Evaluate infrastructure engineering tasks and solutions
• Provide clear, written technical feedback
• Develop guidelines and detailed rubrics for cluster failure diagnosis, IaC design quality, and CI/CD pipeline reasoning
• Collaborate with subject-matter experts to ensure consistency and accuracy in training data

Requirements

This role requires substantial professional experience operating production cloud infrastructure and explaining complex technical decisions in writing. Candidates should be able to diagnose real infrastructure failures rather than only author configuration files or use managed control planes.

• At least 4 years of dedicated professional experience in cloud infrastructure, DevOps, site reliability, or platform engineering
• Professional experience at a recognized, top-tier organization
• Hands-on production Kubernetes operations experience, including diagnosing and repairing cluster failures
• Production experience with Terraform and/or AWS CDK
• Direct production experience integrating AWS Lambda, API Gateway, and DynamoDB
• Experience building and owning CI/CD pipelines
• Demonstrable career progression
• Strong written communication skills
• Ability to explain complex technical decisions clearly
• Reliable availability for at least 40 hours per week during weekdays

Helpful Background

Experience working on AI model training data or evaluation projects is helpful, but the core requirement is deep, hands-on cloud and DevOps expertise that can be applied to technical AI training tasks.

• Previous AI training data experience is a plus
• Experience evaluating technical solutions or creating engineering guidance can support success in the role

How to Apply Through OpenTrain

Create a free OpenTrain account, build your profile around your cloud infrastructure and DevOps experience, and apply to this opportunity in minutes. Highlight production Kubernetes operations, Terraform or AWS CDK work, AWS service integrations, CI/CD ownership, and your technical writing strengths.

• Show evidence of diagnosing and repairing Kubernetes cluster failures
• Describe your production Infrastructure-as-Code experience
• Detail AWS Lambda, API Gateway, and DynamoDB integrations
• Explain the CI/CD pipelines you have built or owned
• Emphasize career progression and clear written communication