Software Engineer (Cloud Performance)

San Jose, CA, US • Posted 6 days ago • Updated 3 hours ago
Full Time
On-site
USD $130,000.00 - 225,000.00 per year
Fitment

Dice Job Match Score™

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Job Details

Skills

  • SaaS
  • Collaboration
  • Scalability
  • Analytical Skill
  • Regression Analysis
  • Capacity Management
  • Optimization
  • Customer Experience
  • Management
  • Performance Analysis
  • Modeling
  • Benchmarking
  • Cloud Computing
  • Performance Engineering
  • Artificial Intelligence
  • Machine Learning (ML)
  • Cloud Storage
  • Operating Systems
  • Data Structure
  • Scripting
  • Python
  • Shell
  • Perl
  • Jupyter
  • Electrical Engineering
  • Computer Science
  • Science
  • Health Insurance
  • Life Insurance
  • Recruiting

Summary

Job Summary

Design, develop, analyze, and optimize cloud software and performance capabilities for cloud storage services and distributed systems. In this role you will collaborate with cross-functional engineering teams to model, measure, analyze, and improve the performance, scalability, and cost-efficiency of cloud platforms-ensuring customer and market requirements are met while balancing quality, cost, and time-to-market. The ideal candidate is systems-focused, analytical and creative, and driven to deliver measurable performance improvements at cloud scale.

Responsibilities

  • Design and execute performance benchmarks/workloads; measure, analyze, interpret, and socialize results to identify improvement opportunities.
  • Apply AI-assisted performance engineering techniques and develop tools (e.g., performance analysis, automated regression triage, and ML-based capacity planning) to accelerate bottleneck analysis and guide optimization priorities.
  • Evaluate design alternatives and prototype performance enhancements across cloud services and distributed components.
  • Collect and analyze customer experience signals and usage patterns; prepare findings and recommendations for engineering and management.

Job Requirements

  • Knowledge of performance analysis, modeling techniques, benchmarking, and workload characterization.
  • Understanding of performance tradeoffs when designing for multi-tenant, elastic cloud environments (latency, throughput, cost, and reliability).
  • Hands-on experience applying AI/ML techniques to performance engineering.
  • Understanding of AI/ML workloads and their impact on cloud storage performance.
  • Strong foundations in operating systems, data structures, and standard programming practices; systems programming in C is highly desirable.
  • Proficiency with scripting and automation (Python, shell; Perl acceptable) and comfort working with notebooks (e.g., Jupyter).

Education

  • A minimum of 5 years of experience is required. 6 to 8 years of experience is preferred.
  • A Bachelor of Science in Electrical Engineering or Computer Science; or equivalent experience is required. Master of Science, or PhD Degrees are preferred.

Compensation:
The target salary range for this position is $130,000-$225,000. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU's), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: cxnetapp
  • Position Id: 6d712c2bf7511631134c49b7ead8c88c
  • Posted 6 days ago
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