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NetApp
Software Engineer SRE (Site Reliability Engineer)
NetApp
Bengaluru•Hybrid•5-8 Yrs•Jun 28
Job description
Hybrid
Overview
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.
Qualifications
- 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
- 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
- Deep familiarity with monitoring and observability tools, including Dynatrace, Grafana, and Prometheus
- Solid understanding of SQL and NoSQL databases, including operations, backup, and monitoring
- 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
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.