Cloud Performance Engineer: AI-Driven Optimization

NetApp; California (MO); Hybrid; USD 148,000 - 220,000; Full time

Job summary

NetApp seeks a performance-focused engineer to design, develop, analyze, and optimize cloud software and performance capabilities for cloud storage services and distributed systems. You will collaborate with cross-functional teams to model, measure, analyze, and improve performance, scalability, and cost-efficiency while balancing quality, cost, and time-to-market.

The ideal candidate is systems-focused, analytical, and creative, with a track record of delivering measurable cloud-scale

Qualifications

• Minimum 4 years of performance engineering experience.
• Knowledge of performance analysis, modeling, benchmarking, and workload characterization.
• Understanding of performance tradeoffs in multi-tenant elastic cloud environments (latency, throughput, cost, reliability).
• Experience applying AI/ML techniques to performance engineering and workloads.
• Strong OS foundations, data structures, and systems programming in C is desirable.
• Proficiency in scripting/automation (Python, shell; Perl acceptable) and familiarity with notebooks (Jupyter).

Responsibilities

• Design and run performance benchmarks and workloads; analyze results and share findings.
• Develop AI-assisted performance engineering tools to accelerate bottleneck analysis and prioritization.
• Evaluate designs and prototype performance improvements across cloud services.
• Collect customer experience signals and usage patterns to inform recommendations.

Skills

Performance analysis

Modeling techniques

Benchmarking

Workload characterization

AI/ML for performance

C programming

OS fundamentals

Scripting/automation

Education

Bachelor/Master/PhD in EE or CS

Tools

Python

Shell

Jupyter

Perl (acceptable)

Job description

NetApp seeks a performance-focused engineer to design, develop, analyze, and optimize cloud software and performance capabilities for cloud storage services and distributed systems. You will collaborate with cross-functional teams to model, measure, analyze, and improve performance, scalability, and cost-efficiency while balancing quality, cost, and time-to-market.

The ideal candidate is systems-focused, analytical, and creative, with a track record of delivering measurable cloud-scale