Cloud / DevOps Engineer (Infra & IaC)

Summary

Weekday AI is seeking an experienced Cloud / DevOps Engineer to support a cutting-edge GenAI environment. The role focuses on evaluating technical workflows, developing reference solutions, and establishing rigorous standards for AI-generated reasoning across cloud infrastructure, Kubernetes, AWS, Infrastructure-as-Code, and CI/CD.

Responsibilities

• Collaborate with research and engineering teams to identify knowledge gaps and improve AI model performance across cloud infrastructure, DevOps, Kubernetes, and Infrastructure-as-Code domains
• Design realistic and technically challenging tasks covering Kubernetes troubleshooting, AWS service integration, infrastructure automation, and production operations
• Develop accurate, detailed reference solutions for complex infrastructure engineering scenarios
• Review and evaluate AI-generated technical solutions for correctness, reliability, scalability, security, and adherence to production best practices
• Provide clear, structured written feedback highlighting technical gaps, incorrect assumptions, and opportunities for improvement
• Create detailed evaluation criteria, rubrics, and benchmarks for assessing Kubernetes troubleshooting, IaC architecture, AWS integrations, and CI/CD reasoning
• Develop scenarios involving cluster failures, infrastructure automation, deployment workflows, service integrations, and operational reliability
• Work closely with other technical subject matter experts to maintain consistency, accuracy, and quality across evaluation datasets
• Translate practical production experience into structured guidance that can be used to improve AI-generated infrastructure solutions

Skills

• **4+ years of professional experience** in Cloud Infrastructure, DevOps, Site Reliability Engineering, Platform Engineering, or a closely related field
• Strong hands-on experience managing **Kubernetes in production environments**, including diagnosing, troubleshooting, and resolving cluster failures and operational issues
• Experience with Kubernetes beyond simply writing manifests or consuming managed Kubernetes control planes
• Proven production experience with **Infrastructure-as-Code**, particularly **Terraform and/or AWS CDK**
• Strong practical knowledge of **AWS cloud services**, including production integration with services such as:
• AWS Lambda
• API Gateway
• DynamoDB
• Experience designing, implementing, and maintaining **CI/CD pipelines** for production workloads
• Strong understanding of cloud architecture, infrastructure automation, deployment strategies, observability, reliability, and operational best practices
• Demonstrated career progression with increasing ownership and responsibility in infrastructure, DevOps, or platform engineering
• Ability to commit reliably to **40 hours per week during standard weekdays**
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts and engineering decisions clearly
• Strong analytical and troubleshooting abilities, particularly when diagnosing distributed systems and infrastructure failures
• Experience working with large-scale cloud infrastructure or highly distributed systems
• Familiarity with Kubernetes networking, security, storage, scaling, and cluster lifecycle management
• Experience implementing infrastructure security and reliability best practices
• Knowledge of AWS architecture patterns and cloud-native application design
• Experience with GitOps, containerization, monitoring, logging, and observability platforms
• Familiarity with modern DevOps and platform engineering methodologies
• Experience reviewing or evaluating technical documentation, engineering solutions, or AI-generated outputs

Qualifications

Must Haves

• **4+ years of professional experience** in Cloud Infrastructure, DevOps, Site Reliability Engineering, Platform Engineering, or a closely related field
• Strong hands-on experience managing **Kubernetes in production environments**, including diagnosing, troubleshooting, and resolving cluster failures and operational issues
• Experience with Kubernetes beyond simply writing manifests or consuming managed Kubernetes control planes
• Proven production experience with **Infrastructure-as-Code**, particularly **Terraform and/or AWS CDK**
• Strong practical knowledge of **AWS cloud services**, including production integration with services such as:
• AWS Lambda
• API Gateway
• DynamoDB
• Experience designing, implementing, and maintaining **CI/CD pipelines** for production workloads
• Strong understanding of cloud architecture, infrastructure automation, deployment strategies, observability, reliability, and operational best practices
• Demonstrated career progression with increasing ownership and responsibility in infrastructure, DevOps, or platform engineering
• Ability to commit reliably to **40 hours per week during standard weekdays**
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts and engineering decisions clearly
• Strong analytical and troubleshooting abilities, particularly when diagnosing distributed systems and infrastructure failures

Nice to Haves

• Experience working with large-scale cloud infrastructure or highly distributed systems
• Familiarity with Kubernetes networking, security, storage, scaling, and cluster lifecycle management
• Experience implementing infrastructure security and reliability best practices
• Knowledge of AWS architecture patterns and cloud-native application design
• Experience with GitOps, containerization, monitoring, logging, and observability platforms
• Familiarity with modern DevOps and platform engineering methodologies
• Experience reviewing or evaluating technical documentation, engineering solutions, or AI-generated outputs