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Principal Engineer - Cloud Architecture, AI-Driven Operations & SaaS Platform Engineering
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Principal Engineer - Cloud Architecture, AI-Driven Operations & SaaS Platform Engineering
NETAPPEarly Applicant
- Posted 28 days ago
- Be among the first 10 applicants
Job Description
Job Summary
NetApp is seeking an experiencedPrincipal Engineerto provide technical leadership for the NetApp Console SaaS platform, with ownership across cloud architecture, reliability, observability, FinOps, and AI-driven operations.
This role will define the long-term platform strategy, guide architectural decisions, and partner with Engineering, Product, SRE, Cloud Operations, and leadership teams to build scalable, secure, resilient, and cost-efficient cloud services
Job Requirements
Key Responsibilities
- Define the technical architecture and roadmap for NetApp Console SaaS.
- Lead the design of cloud-native services that are scalable, secure, highly available, and resilient.
- Own platform reliability, scalability, performance, and operational readiness.
- Define and manage SLIs, SLOs, SLAs, error budgets, and operational KPIs.
- Drive adoption of AI Agents and AIOps solutions for DevOps, SRE, incident response, root cause analysis, and remediation.
- Promote self-healing infrastructure, predictive operational models, and automation to improve efficiency and reliability.
- Lead observability strategy across applications, infrastructure, and customer-facing services.
- Establish best practices for monitoring, alerting, incident management, and operational analytics using platforms such as Dynatrace, Grafana, ELK Stack, and OpenTelemetry.
- Own cloud capacity planning, forecasting, utilization, and cost optimization strategies.
- Provide visibility into cloud spend, growth trends, governance gaps, and optimization opportunities.
Education
- BS/MS in Computer Science, Engineering, or related field.
- 15+ years of experience in software engineering, cloud architecture, platform engineering, SRE, or cloud operations.
More Info
About Company
Skills:
Performance Tuning, Kafka, Spark, Apache Iceberg, Debezium, object-store-based data architectures, CockroachDB, columnar database architecture, Flink, Beam, Vitess, distributed relational databases, batch data pipelines