Back to SearchSenior AI Infrastructure Engineer
Remote in Latvia, Republic of Lithuania
DevOps& 13 others
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We are looking for a highly skilled Senior AI Infrastructure Engineer to design, build, operate, and optimize scalable infrastructure that supports enterprise AI/ML platforms and workloads. The ideal candidate will have deep expertise in cloud-native technologies, Kubernetes, observability, automation, and platform reliability, with a strong focus on enabling AI/ML teams through robust and efficient infrastructure.
Responsibilities
- Design, build, operate, and optimize scalable infrastructure supporting enterprise AI/ML platforms and workloads
- Manage and maintain containerized applications and orchestration platforms to ensure high availability and performance
- Provide operational support for mission-critical production environments
- Troubleshoot infrastructure, platform, application, and container orchestration issues
- Perform log analysis, root cause analysis (RCA), and incident management
- Implement and maintain monitoring, logging, and observability solutions across platforms
- Enable AI/ML teams through robust automation, tooling, and efficient infrastructure practices
- Optimize system design for scalability, performance, and reliability
- Collaborate on networking configurations, including load balancing, ingress, and traffic management
- Apply cloud-native architecture patterns and platform engineering best practices across environments
Requirements
- Bachelor's degree in Engineering (B.E/B.Tech) or a related field with 5+ years of relevant experience
- Hands-on expertise in Kubernetes, Docker, and containerized application management
- Experience managing infrastructure on at least one major cloud platform (Azure, AWS, or GCP)
- Proficiency in scripting and automation using Python, Shell/Bash, or similar languages
- Familiarity with monitoring, logging, and observability tools such as Prometheus, Grafana, and ELK/OpenSearch or Datadog
- Strong understanding of Linux systems administration and platform operations
- Knowledge of system design, scalability, performance optimization, and reliability engineering
- Capability to perform troubleshooting, log analysis, root cause analysis (RCA), and incident management
- Understanding of networking fundamentals, including DNS, load balancing, and ingress and security concepts
- Background in supporting AI/ML platforms or GPU-based workloads in production environments
- Expertise in advanced networking concepts such as service mesh (Istio/Linkerd), network policies, and API gateways
- Skills in cloud-native architecture patterns combined with strong analytical and troubleshooting abilities
- English proficiency at an Upper-Intermediate level (B2) or higher
Nice to have
- Familiarity with SRE practices (SLIs, SLOs, error budgets, disaster recovery)
- Hands-on experience with Infrastructure as Code tools such as Terraform and Helm Charts
- Experience in cloud cost monitoring and optimization for high-compute AI workloads