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, and operate scalable infrastructure supporting enterprise AI/ML platforms and workloads Manage and maintain Kubernetes and Docker environments for containerized applications Operate and optimize infrastructure on cloud platforms to support AI/ML workloads Develop automation scripts and tools to streamline platform operations Implement and maintain monitoring, logging, and observability solutions across infrastructure Administer Linux systems and ensure reliable platform operations Apply system design principles to improve scalability, performance, and reliability Troubleshoot infrastructure, platform, application, and container orchestration issues Conduct log analysis, root cause analysis, and incident management for production issues Configure and maintain networking components, including DNS, load balancing, ingress, and security controls Provide operational support for mission-critical production environments Requirements Bachelor's degree in Engineering (B.Tech/B.E.) with 5+ years of relevant experience Expertise in Kubernetes and Docker for container orchestration and management Experience managing infrastructure on at least one major cloud platform (Azure, AWS, or GCP) Proficiency in scripting and automation using Python, Shell, or Bash Familiarity with monitoring, logging, and observability tools such as Prometheus, Grafana, and ELK/OpenSearch or Datadog Understanding of Linux systems administration and platform operations Knowledge of system design, scalability, performance optimization, and reliability engineering Skills in troubleshooting infrastructure, platform, application, and container orchestration issues Capability to perform log analysis, root cause analysis, and incident management Understanding of networking fundamentals, including DNS, load balancing, ingress, and security concepts Background in providing operational support for mission-critical production environments Nice to have Background in supporting AI/ML platforms or GPU-based workloads Knowledge of advanced networking concepts such as service mesh (Istio/Linkerd), network policies, API gateways, and traffic management Familiarity with cloud-native architecture patterns and platform engineering best practices Familiarity with SRE practices, including SLIs, SLOs, error budgets, and 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
