Software Engineer SRE (Site Reliability Engineer)

Job Summary

We’re looking for a Site Reliability Engineer, focused on building and operating the data and AI/ML infrastructure platform that powers NetApp’s cloud-native data services. You’ll work at the intersection of software engineering and infrastructure operations — designing systems for reliability, driving automation, and ensuring our platforms meet the highest availability standards for customers worldwide.

This is an infrastructure-focused SRE role, you’ll own the reliability of large-scale Kubernetes clusters (including GPU workloads), streaming data pipelines (Kafka), and analytical compute infrastructure (Spark, Dremio) across hybrid-cloud and multi-cloud environments.

Job Requirements

• 5+ years in SRE, DevOps, Platform Engineering, or Infrastructure Engineering roles
• Extensive experience with Linux (RHEL/CentOS), including shells, filesystems, kernel tuning, networking, and performance optimization
• Deep expertise with Kubernetes at scale, including cluster administration, troubleshooting, networking, storage, RBAC, and lifecycle management (on-premises and Rancher Kubernetes)
• Hands-on experience operating GPU workloads on Kubernetes, including NVIDIA GPU Operator, device plugins, scheduling, and resource management
• Strong experience managing Confluent Kafka in production, including operations, monitoring, performance tuning, and disaster recovery
• Experience operating Apache Spark and/or Dremio, including cluster management, job scheduling, scaling, and performance optimization
• Proficiency in Infrastructure as Code using Terraform, Helm, and GitOps workflows with ArgoCD/FluxCD
• Proficiency in scripting and automation using Shell, Ansible, and Python, with a strong automation-first mindset
• Experience with scheduling and orchestration tools such as cron jobs and Apache Airflow
• Deep familiarity with monitoring and observability tools, including Dynatrace, Grafana, and Prometheus
• Solid understanding of SQL and NoSQL databases, including operations, backup, and monitoring
• Experience designing and maintaining CI/CD pipelines and release processes
• Expertise in AWS cloud platforms and hybrid-cloud integration
• Strong systems thinking, with an understanding of how infrastructure design choices impact failure modes, scalability, and recovery
• Strong incident management skills and post-mortem facilitation experience
• Excellent written communication skills for design documents, runbooks, post-mortems, and operational documentation

Nice to Have

• Knowledge of Generative AI tools and frameworks, including the application of AI-based predictive analytics and automation in infrastructure operations
• Familiarity with ML platforms such as Kubeflow, MLflow, and Ray, as well as AI/ML training infrastructure
• Experience with Kafka Streams, ksqlDB, or Apache Flink

Education

• 5-8 years of relevant experience.
• Bachelor of Science Degree in Computer Science, Electrical Engineering, or a related field; a Master’s Degree is preferred.