Cloud / DevOps Engineer, Infra & IaC

🕒 Setembro 3

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $75 - $110 / hora

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

⛑ DevOps & Engenheiro de Confiabilidade do Site (SRE)

👻 Score fantasma 20%

O que significa: quão provável esta vaga está aberta sem contratação ativa.Como ler: 60% ou mais significa que achamos que é uma vaga fantasma. Pontuações mais baixas preocupam menos.Como pontuamos: tempo em aberto, republicações, vagas abertas vs tamanho do time, rapidez para fechar vagas, e se o salário está divulgado.Observação: é uma estimativa de dados públicos, não um julgamento da empresa. Vagas reais podem ter pontuação alta, então use como uma dica, não como um fato.

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Weekday (YC W21)

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2021

💼 Consultoria

👥 RH Tech

☁️ SaaS

Consulting • HR Tech • SaaS

A Weekday é uma plataforma moderna de recrutamento que combina tecnologias de IA com um vasto banco de dados de potenciais candidatos, com o objetivo de agilizar e simplificar o processo de contratação para empresas na Índia. A empresa oferece diversos serviços, incluindo uma abordagem proativa de outreach que ajuda empregadores a se conectarem com talentos de ponta, além de ferramentas para que candidatos se candidatem facilmente a vagas. O foco da Weekday em engajamento de candidatos por múltiplos canais — incluindo e-mail, WhatsApp e ligações telefônicas — a diferencia no competitivo mercado de agências de recrutamento.

Descrição

• 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

🎯 Requisitos

• 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