Remote Senior Infrastructure Engineer

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Workato

πŸ“Remote - Bulgaria

Job highlights

Summary

Join Workato as a Senior Infrastructure Engineer and be part of a small, flexible team that closely works with ML Engineers and Data Scientists to deploy, scale, and maintain services at the ML/AI team. As a key member, you will have a direct impact on the process of modernization and maturation of the platform, including infrastructure architecture decisions.

Requirements

  • 7+ years professional experience in hands-on engineering roles (DevOps/SRE)
  • BS or MS in the CS field (or equivalent experience)
  • 1+ year of experience with hosting AI models
  • 1+ year of experience with ML Ops
  • Kubernetes Expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service)
  • Programming Skills: Proficiency in Python language is essential
  • CI/CD Tools: Experience creating scalable development and integration pipelines using CI/CD tools such as GitHub Actions, Argo Workflows, GitLab CI, or similar solutions
  • Kubernetes Deployments: Expertise in deploying Kubernetes-based services using tools like Kustomize, Helm, ArgoCD, or similar, following a GitOps approach
  • Cloud Architectures: Hands-on experience with cloud-based architectures, particularly Amazon Web Services (AWS)
  • Networking and Web Services: Strong understanding of networking fundamentals and web services architecture
  • Infrastructure as Code: Experience managing complex infrastructure, including Kubernetes clusters, VPC networking, and security policies, using Infrastructure as Code tools like Terraform
  • Containerization: Hands-on experience with containers, including creating and optimizing Dockerfiles, using docker-compose, and a deep understanding of related technologies (kernel features, container networking, image structure, and registry)
  • Software Packaging and Testing: Familiarity with software packaging tools, functional testing, security validation tools and services, and code coverage tools
  • Compliance and Security: Operating Kubernetes clusters in compliance-regulated environments and understanding kernel-level container technologies such as seccomp, namespaces, and cgroups
  • Security Regulations and Compliance: Experience with cloud and infrastructure security regulations and compliance programs, including SOC2, ISO27001, HIPAA, GDPR, and CCPA
  • Good communication and collaboration skills in international technological companies
  • Readiness to work remotely with teams distributed across the world and timezones
  • Good Spoken English to participate in product-related, architectural and technical discussions

Responsibilities

  • Deploying, scaling, and maintenance of services at the ML/AI team
  • Closely working with ML Engineers and Data Scientists as a part of a small, flexible team
  • Having a direct impact on the process of modernization and maturation of the platform, including infrastructure architecture decisions

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