AI Infra Cloud & DevOps Engineer | Kubernetes & CI/CD

Netrolynx AI; United States; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Health insurance

Retirement savings

Paid time off

Continuous learning and development

Job summary

Mercor's AI research and development team seeks a Cloud and DevOps Engineer to build and maintain the infrastructure that supports large-scale AI models. You will optimize cloud systems, operate Kubernetes clusters, and automate infrastructure using Terraform and AWS CDK, enabling reliable training and deployment of state-of-the-art language models.

You will work closely with researchers and engineers to ensure scalable, secure, and observable infrastructure while contributing to the AI

Qualifications

• 4+ years in cloud infrastructure, DevOps, or platform engineering.
• Hands-on Kubernetes cluster operations for high availability.
• Experience with IaC—Terraform or AWS CDK—and AWS services.

Responsibilities

• Collaborate with research and engineering teams to improve AI model deployment in cloud and Kubernetes.
• Design tasks for cluster diagnosis, cloud service integration, and automation.
• Review infra engineering tasks and provide detailed feedback.
• Develop guidelines and rubrics to assess cluster diagnostics and CI/CD quality.
• Work with experts to ensure quality in training data and infrastructure processes.

Skills

Cloud infrastructure

Site reliability engineering

Platform engineering

Written communication

40-hour workweek commitment

Tools

Kubernetes

Terraform

AWS CDK

AWS Lambda

API Gateway

DynamoDB

CI/CD pipelines

Job description

Mercor's AI research and development team seeks a Cloud and DevOps Engineer to build and maintain the infrastructure that supports large-scale AI models. You will optimize cloud systems, operate Kubernetes clusters, and automate infrastructure using Terraform and AWS CDK, enabling reliable training and deployment of state-of-the-art language models.

You will work closely with researchers and engineers to ensure scalable, secure, and observable infrastructure while contributing to the AI