Cloud / DevOps Engineer, Infra & IaC

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $75 - $110 / hour

⏰ Full Time

🟡 Mid-level

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Weekday (YC W21)

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💼 Consulting

👥 HR Tech

☁️ SaaS

Consulting • HR Tech • SaaS

Weekday is a modern recruitment platform that combines AI technologies with a vast database of potential candidates, aiming to streamline the hiring process for companies in India. They offer various services, including a proactive outreach approach that helps employers connect with top talent, as well as tools for candidates to easily apply for jobs. Weekday's emphasis on candidate engagement through multiple channels, including email, WhatsApp, and phone calls, sets it apart in the competitive landscape of recruitment agencies.

📋 Description

• 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 • Establish high-quality standards for AI systems working with complex Cloud, DevOps, Kubernetes, AWS, and IaC problems • Transform practical engineering knowledge into structured tasks, reference solutions, evaluation frameworks, and technical feedback to improve next-generation AI models

🎯 Requirements

• 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 AWS Lambda, API Gateway, and 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