Software Engineer III - Asset Management (hybrid)

CrowdStrike CrowdStrike · Enterprise · Sunnyvale, CA

Software Engineer III role focused on building and maintaining backend microservices for CrowdStrike's Asset Management product, which provides centralized visibility into asset usage and application inventory. The role emphasizes writing secure and maintainable Golang code, collaborating across teams, and ensuring quality through testing, logging, and metrics. While not directly building AI models, the role requires hands-on daily experience with AI tools like ChatGPT and GitHub Copilot, integrating them into workflows, and understanding AI capabilities and limitations.

What you'd actually do

  1. Write secure and maintainable code that powers one of CrowdStrike’s flagship products
  2. Collaborate with others across multiple teams to brainstorm, research, and build solutions that are driven by our Product roadmap
  3. Build, maintain, and improve backend microservices written in Golang
  4. Launch and support features that will be used by millions of users around the world
  5. Understand business and engineering requirements so that you can be proactive in sharing ideas and solutions

Skills

Required

  • Golang
  • Kafka
  • Cassandra
  • distributed systems
  • platform services
  • micro-service architectures
  • multi-region architectures
  • software development best practices
  • observability
  • reliability engineering
  • scalability
  • queues
  • concurrency
  • sharding
  • partitioning
  • AI tools (ChatGPT, GitHub Copilot)
  • integrating AI into workflows
  • understanding of AI capabilities, limitations, and responsible usage practices
  • testing paradigms
  • peer code reviews
  • resilient architecture
  • debugging complex issues

Nice to have

  • Docker
  • Kubernetes
  • cybersecurity industry

What the JD emphasized

  • production-level experience in building, delivering, and maintaining systems at scale
  • Expertise in distributed systems, platform services, mirco-service architectures, multi-region architectures, software development best practices, observability and reliability engineering
  • Expertise in scalability such as queues, concurrency, sharding, partitioning, etc.
  • Hands-on daily experience with AI tools such as ChatGPT, GitHub Copilot, Cloud code or similar platforms
  • Proven ability to integrate AI into daily workflows to improve efficiency and outcomes
  • Understanding of AI capabilities, limitations, and responsible usage practices