Senior Distributed Systems Engineer, NG-SIEM & Serverless

CrowdStrike Inc.; Australia; Remote; AUD 140,000 - 190,000; Full time

Job summary

CrowdStrike Inc. is seeking an experienced engineer for a fully remote role based in Australia.

The role focuses on large-scale distributed systems, intelligent placement, autobalancing, and autoscaling to deliver high performance with efficient resource use. Ideal candidates will have 5+ years building and maintaining software in a SaaS environment, with hands-on experience managing systems that process billions of requests daily and store vast data.

Qualifications

• 5+ years designing, implementing, and maintaining multiple software systems across SaaS environments.
• Hands-on experience as an engineer in distributed systems handling large-scale data and traffic.
• Proven impact on customer experience and business results.
• Experience leveraging AI to improve decision-making and efficiency.
• Excellent communication in a remote, global team.

Responsibilities

• Decide how customers land on fleet segments and optimize resource allocation.
• Continuously rebalance customers across shared infrastructure to maintain performance.
• Manage autoscaling to adapt capacity with real usage.
• Use real-time per-tenant metrics to drive placement and balance decisions.
• Dive into the data platform to understand ingestion, storage, and query behavior.
• Contribute to reliability, incident response, and feature delivery for LogScale.

Skills

Distributed systems

Autobalancing

Autoscaling

Data-driven decisions

Operational rigor

Technical strategy

Job description

CrowdStrike Inc. is seeking an experienced engineer for a fully remote role based in Australia.

The role focuses on large-scale distributed systems, intelligent placement, autobalancing, and autoscaling to deliver high performance with efficient resource use. Ideal candidates will have 5+ years building and maintaining software in a SaaS environment, with hands-on experience managing systems that process billions of requests daily and store vast data.