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OpenTrain AI is seeking a remote AWS Serverless and Infrastructure-as-Code Task Auditor to evaluate cloud architecture tasks used for AI model training. You will assess multi-service AWS serverless work for correctness, reliability, and maintainability, focusing on practical implementation in real AWS environments.
The role is remote for US-based workers, with a commitment of 20+ hours per week (40 hours default) and pay of $70–$90 per hour.
OpenTrain AI is hiring contractors for specialized AI training projects that help improve advanced artificial intelligence systems. OpenTrain helps people discover meaningful work in AI training, build a professional portfolio, and grow flexible careers in this fast-moving field.
In this role, you will bring your AWS expertise to technical evaluation work that influences the quality of data used to train and assess frontier AI models.
AI training is the human side of building artificial intelligence. Specialists review examples, assess model outputs, and provide structured feedback so AI systems can become more accurate, reliable, and useful.
Technical auditors play an important role by checking whether coding tasks are correct, realistic, and suitable for model training and evaluation. Your cloud architecture judgment will help identify high-quality examples and expose errors in implementation or reasoning.
OpenTrain is recruiting an AWS Serverless and Infrastructure-as-Code Task Auditor to evaluate cloud architecture tasks used to train and assess frontier AI models. You will assess the quality, correctness, and technical soundness of serverless and infrastructure-as-code work using structured written judgment.
This freelance role is suited to someone with at least three years of hands-on experience building multi-service AWS serverless applications and strong practical experience with AWS CDK, CloudFormation, or SAM.
You will review both architecture and implementation details, with particular attention to how services work together in real-world AWS environments. Your assessments should distinguish technically correct solutions from implementations that only appear to work in local testing.
Feedback should be clear, structured, and grounded in the applicable rubric. The goal is to evaluate task quality, correctness, and usefulness for AI model training and assessment.
You should be able to reason carefully about distributed, event-driven systems and explain technical findings in concise written feedback. Strong practical AWS experience is essential because the work requires evaluating both architecture decisions and implementation behavior.
Several qualifications are helpful but are not listed as required: AWS Solutions Architect or Developer certification, experience with observability and cost optimization for serverless workloads, and previous code review or task-grading experience.
This remote contract role is available to workers in the United States. The expected commitment is at least 20 hours per week, with a default schedule of 40 hours per week.
The compensation range is $70-$90 per hour.