Senior Infrastructure Architect
2 semanas atrás
About the Role
As a Senior Infrastructure Engineer at Workato, you will be responsible for designing, deploying, and maintaining scalable and secure services at the ML/AI team. You will collaborate closely with ML Engineers and Data Scientists as part of a dynamic and flexible team, driving the modernization and maturation of our platform through infrastructure architecture decisions.
Our Team
Our ML/AI team is a unique group of international, senior-level professionals experienced in building high-performing, scalable, enterprise-grade applications. We are committed to fostering a flexible, trust-oriented culture that empowers everyone to take ownership of their roles, balancing productivity with self-care.
Requirements
- 7+ years of professional experience in hands-on engineering roles (DevOps/SRE) with a BS or MS in Computer Science or equivalent experience
- 1+ year of experience with hosting AI models (ML flow, AWS Sagemaker, Azure AI, Kubernetes)
- 1+ year of experience with ML Ops (ML flow, vector databases, dagster)
- Kubernetes Expertise: Strong experience managing Kubernetes clusters and workloads, specifically using EKS (Elastic Kubernetes Service)
- Programming Skills: Proficiency in Python language is essential, with the ability to program in other languages such as Go, Ruby, or JavaScript a plus
- 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
- Soft Skills / Personal Characteristics: Good communication and collaboration skills in international technological companies, readiness to work remotely with teams distributed across the world and timezones, and good Spoken English to participate in product-related, architectural, and technical discussions
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