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
