DevOps Engineer

8 hours ago

Dublin, Dublin City, Ireland beBeeDevops Full time €100,000 - €110,000

Join us as a Staff DevOps Engineer to build the automated backbone of our AI platform. Drive continuous delivery, resilient infrastructure, and high-performance AI workloads with cutting-edge DevOps, DevSecOps, and MLOps practices.

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  • Develop CI/CD pipelines for rapid, reliable delivery of AI platform components and intelligent agents
  • Implement Infrastructure as Code (IaC) and GitOps practices for scalable, secure, and reproducible environments
  • Build and manage Kubernetes-based infrastructure, including custom operators and GPU workload orchestration
  • Integrate MLOps tools and workflows to streamline the AI model lifecycle from training to deployment
  • Deploy and maintain observability stacks for real-time monitoring, tracing, and alerting across distributed systems
  • Enforce DevSecOps practices, including automated security scanning, policy-as-code, and compliance automation
  • Optimize cloud infrastructure for performance, cost-efficiency, and resilience

You will lead the implementation of these practices, ensuring our platform is production-ready, cost-efficient, and built for speed, security, and scale. As a key member of our team, you will drive continuous improvement across the stack and collaborate with cross-functional teams to achieve our goals.

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To succeed in this role, you will need:

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  • 5-7+ years of experience in DevOps, SRE, or platform engineering
  • Expert-level knowledge of CI/CD pipeline design and tools (e.g., Jenkins, GitLab CI, ArgoCD, GitHub Actions)
  • Deep understanding of Infrastructure as Code (IaC) concepts and tools (e.g., Terraform, CloudFormation)
  • Advanced knowledge of Kubernetes administration and workload management, including custom controllers/operators
  • Experience with MLOps tools and platforms (e.g., Kubeflow, MLflow, Seldon Core, Vertex AI Pipelines, SageMaker MLOps)
  • Proficiency in implementing observability stacks (e.g., Prometheus, Grafana, Jaeger, OpenTelemetry, ELK)
  • Strong scripting skills (Python, Bash, Go)
  • Understanding of cloud security best practices and automation (e.g., SAST, DAST)
  • Experience with GitOps workflows and cost optimization strategies for cloud-based AI/ML workloads
  • Bachelor's degree in Computer Science, DevOps Engineering, or a related field

Additional certifications, such as Certified Kubernetes Administrator (CKA), DevOps Engineer certifications (AWS, Azure, GCP), or FinOps certification, are a plus. If you have experience with GPU cluster management and scheduling, infrastructure for federated learning or edge AI, proficiency in policy-as-code frameworks, AI model serving optimization and inference acceleration, or building and managing serverless infrastructure for AI, that would be great too.

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Kaseya provides equal employment opportunity to all employees and applicants without regard to race, religion, age, ancestry, gender, sex, sexual orientation, national origin, citizenship status, physical or mental disability, veteran status, marital status, or any other characteristic protected by applicable law.

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