AWS Serverless Infrastructure-as-Code Task Auditor

About OpenTrain

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.

• Remote contract opportunity for workers in the United States
• Flexible freelance work with a default commitment of 40 hours per week
• 20+ hours per week required
• $70-$90 per hour

About AI Training and Technical Evaluation

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.

• Apply professional cloud expertise to cutting-edge AI development
• Evaluate technical work against structured quality criteria
• Help improve how AI systems understand AWS architecture and code

The AWS Serverless Task Auditor Role

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.

• Role: AWS Serverless and Infrastructure-as-Code Task Auditor
• Work arrangement: Remote contract
• Location: United States
• Language: English
• Experience requested: At least three years of hands-on AWS serverless development

What You'll Evaluate

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.

• Multi-service serverless architectures using Lambda and API Gateway
• DynamoDB and Streams, S3, EventBridge, SNS or SQS, and Step Functions
• AWS CDK, CloudFormation, and SAM implementations
• Infrastructure-as-code fidelity, correctness, and maintainability
• Event-driven behavior and cross-service integration
• IAM permissions and permission boundaries
• Failure handling and retry semantics
• LocalStack or similar emulation compared with expected real AWS behavior

Required Skills and Helpful Experience

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.

• At least three years of hands-on experience building multi-service AWS serverless applications
• Strong practical expertise with Lambda, API Gateway, DynamoDB or Streams, S3, EventBridge, SNS or SQS, and Step Functions
• Proficiency with AWS CDK, CloudFormation, or SAM
• Ability to assess event-driven correctness, IAM boundaries, and failure or retry semantics
• Familiarity with LocalStack or similar local AWS emulation
• Understanding of differences between local emulation and real AWS behavior
• Clear, structured written judgment
• Helpful: AWS Solutions Architect or Developer certification
• Helpful: observability, cost optimization, code review, or task-grading experience

Schedule, Pay, and Application

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. Create a free OpenTrain account and apply in minutes to bring your AWS serverless expertise to AI training work.

• Pay: $70-$90 per hour
• Minimum time requirement: 20+ hours per week
• Default commitment: 40 hours per week
• Eligible location: United States
• Apply through OpenTrain