DEVOPS ENGINEER - AI TECH – INGLES – REMOTO

IRIUM; Murcia; A distancia; EUR 40.000 - 60.000; Jornada completa

Descripción de la vacante

A leading tech company is seeking a DevOps Engineer to design and manage CI/CD pipelines for AI projects. This role requires 5+ years of experience, strong skills in cloud environments, and familiarity with containerization tools like Docker and Kubernetes. The position is fully remote within Spain, offering a chance to work on cutting-edge AI technologies and enhance your career in a mid-senior level role.

Formación

• 5+ years of experience in relevant roles.
• Strong background in cloud environments.
• Experience implementing CI/CD pipelines.

Responsabilidades

• Design and manage CI/CD pipelines for AI models.
• Build and maintain cloud-native infrastructure.
• Automate infrastructure provisioning using IaC tools.

Conocimientos

5+ years of experience in DevOps, Site Reliability Engineering, or Platform Engineering roles

Hands-on experience with Docker and Kubernetes

Background in managing cloud environments (AWS, Azure, or GCP)

Experience with CI / CD pipelines

Familiarity with machine learning workflows

Strong scripting and automation skills

Experience with monitoring and logging tools

Understanding of security and compliance in cloud-based systems

Ability to translate operational needs into solutions

Excellent communication skills

Educación

Relevant certifications in cloud or DevOps practices

Herramientas

Jenkins

GitHub Actions

GitLab CI

Terraform

CloudFormation

Pulumi

Descripción del empleo

DEVOPS ENGINEER - AI TECH – REMOTO

Posted 5 days ago. Be among the first 25 applicants.

• 5+ years of experience in DevOps, Site Reliability Engineering, or Platform Engineering roles
• Hands-on experience with containerization (Docker, Kubernetes) and orchestration of microservices
• Strong background in managing cloud environments (AWS, Azure, or GCP), including cost optimization and security best practices
• Solid experience implementing CI / CD pipelines and using tools such as Jenkins, GitHub Actions, GitLab CI, or similar
• Familiarity with machine learning workflows, model deployment patterns, and MLOps tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI)
• Relevant certifications in cloud platforms or DevOps practices (e.g., AWS DevOps Engineer, Azure DevOps, Google Cloud DevOps) are a plus
• Strong scripting and automation skills (e.g., Python, Bash, Go)
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack, Datadog)
• Deep understanding of CI / CD and infrastructure automation principles
• Knowledge of security and compliance in cloud-based and AI-driven systems
• Experience working in agile, cross-functional teams focused on rapid delivery and continuous improvement
• Ability to translate operational needs into scalable and maintainable solutions
• Strong problem-solving skills, ownership mindset, and a proactive attitude
• Excellent communication skills and ability to collaborate with both technical and non-technical stakeholders

Responsibilities:

• Design, implement, and manage robust CI / CD pipelines for AI / ML models and GenAI applications
• Build and maintain cloud-native infrastructure (AWS, Azure, or GCP) to support the full AI lifecycle: from data ingestion and model training to production deployment and monitoring
• Automate infrastructure provisioning using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Pulumi
• Ensure scalability, reliability, and high availability of AI services in production environments
• Implement and enforce best practices in MLOps, including model versioning, monitoring, rollback, and automated testing
• Collaborate with data engineering and ML teams to operationalize AI models and integrate them into business-critical systems
• Monitor system performance, debug issues, and lead root-cause analysis and resolution of incidents
• Champion security, compliance, and governance standards across the AI tech stack
• Contribute to the continuous improvement of DevOps capabilities and tooling within the AI Tech Team
• Act as a technical advisor in DevOps and MLOps practices, fostering a culture of automation and engineering excellence

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• Seniority level: Mid-Senior level

Employment type:

• Full-time

Job function:

• Engineering and Information Technology

Industries: Internet Publishing

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