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RevStar

DevOps Forward Deployed Engineer

Cloud EngineeringConfirmed live in the last 24 hours
Full-timeRemote in VenezuelaNo salary listed

About the Job

Requirements

  • At least 7 years of experience designing, deploying, and maintaining enterprise cloud infrastructure in Cloud and DevOps Engineering.
  • At least 5 years of hands-on experience across Anthropic, OpenAI, or AWS environments, serverless architectures, and containerized workloads.
  • At least 3 years of experience in consulting or client-facing roles, including autonomously leading workload assessments, architecting cloud adoption roadmaps, and driving client engagements with minimal oversight.
  • Advanced expertise in Terraform, container orchestration such as AWS ECS/EKS or equivalent cloud container services, and automated provisioning.
  • Expertise in building secure, automated pipelines using GitHub Actions, Azure DevOps, or cloud-native tooling, including integrated static and dynamic application security testing, policy-as-code, and automated testing.
  • Experience with cloud and AI security baselines, including least-privilege identity and access management, guardrails, compliance automation, and cost-optimization frameworks.
  • Professional-level cloud, DevOps, or AI certifications are strongly preferred, such as AWS Certified DevOps Engineer – Professional, Solutions Architect – Professional, security or AI Practitioner specialty certifications, or equivalent Anthropic, OpenAI, or cloud-platform credentials.
  • Strong verbal, written, and presentation skills, including facilitating technical workshops and presenting complex architectures to stakeholders.

Responsibilities

  • Architect, deploy, and manage scalable cloud and AI environments using services such as AWS ECS, EKS, Lambda, S3, API Gateway, or AI platform services, while ensuring security, reliability, and cost-efficiency.
  • Build automated continuous integration and continuous delivery pipelines and version-controlled infrastructure as code using Terraform, GitHub, Azure DevOps, and cloud or AI tooling.
  • Implement proactive monitoring, logging, and alerting across multi-cloud and AI infrastructure environments to optimize performance and prevent operational incidents.
  • Lead discovery workshops, demonstrate solutions, gather technical requirements, and establish credibility with enterprise client stakeholders.
  • Collaborate directly with client stakeholders to align cloud and AI strategies with business outcomes.

Desired Qualifications

  • Professional-level cloud, DevOps, or AI certifications are strongly preferred, including AWS Certified DevOps Engineer – Professional, Solutions Architect – Professional, security or AI Practitioner specialty certifications, or equivalent Anthropic, OpenAI, or cloud-platform credentials.

About the Company

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