Sr. Engineer - Cloud Backend; Hybrid; Sunnyvale

As a global leader in cybersecurity, Crowd Strike protects the people, processes and technologies that drive modern organizations. Since 2011, our mission hasn’t changed — we’re here to stop breaches, and we’ve redefined modern security with the world’s most advanced AI-native platform. We work on large scale distributed systems, processing almost 3 trillion events per day and this traffic is growing daily.

Our customers span all industries, and they count on Crowd Strike to keep their businesses running, their communities safe and their lives moving forward. We're proud to work for a mission-driven company leveraging AI to transform the way we work. Crowd Strikers drive their careers through flexibility and autonomy while also being expected to contribute to a culture of responsible AI adoption, experimentation, and innovation.

We use an AI-first mindset as a force multiplier to proactively and continuously accelerate execution, build expertise, uncover insights, and solve complex problems. We’re always looking to add talented Crowd Strikers to the team who have limitless passion, a relentless focus on innovation and a fanatical commitment to our customers, our community and each other. Ready to join a mission that matters?

The future of cybersecurity starts with you.

This is a full stack backend engineering position on the Spotlight platform team. You will design, build, and operate the cloud-native services and infrastructure that power Crowd Strike's endpoint vulnerability assessment capabilities at global scale. This role requires a strong focus on distributed systems, service reliability, scalability, and cloud architecture across AWS and GCP. This role also requires reasoning and judgment over large volumes of continuously changing data, at the scale Crowd Strike operates — work that conventional rule-based systems have only partially addressed.

We're treating agentic reasoning as a core architectural element rather than a feature layered onto an existing system, which means real decisions are still open: where reasoning belongs, where determinism is the better answer, and how to make either hold up in production. We're treating agentic reasoning as a core architectural element rather than a feature layered onto an existing system, which means real decisions are still open: where reasoning belongs, where determinism is the better answer, and how to make either hold up in production.

• Design and build high-throughput, low-latency backend services and APIs in Golang and Python
• Architect and operate cloud-native infrastructure across AWS and GCP at scale (S3, SQS, Kubernetes/KEDA, and more)
• Build and maintain Kafka-based event streaming pipelines for near-real-time vulnerability event processing
• Drive backend engineering and process automation across the platform
• Partner with security researchers and platform teams (Intel, EPP) to deliver integrated capabilities
• Own service reliability — performance profiling, incident response, and root cause analysis on time-sensitive production issues
• Continuously re-engineer for improved architecture, performance, and stability
• Write high-quality, well-tested, production-ready code with a focus on observability and operability
• Build agentic capabilities into the product — systems that reason over real data, use tools, and produce explainable results customers can act on
• Take AI capabilities from prototype to production, owning latency, cost, correctness, and evaluation
• Design the guardrails and policies that make autonomous reasoning safe for enterprise customers

• 8-12 years of backend engineering experience. Solid experience with Golang/Java in production systems. Strong understanding of distributed systems, microservices, and event-driven architectures. Hands-on experience with AWS cloud services (S3, SQS, and similar) Experience with Kafka or other event streaming platforms. Strong database skills — Cassandra, Elasticsearch/Open Search, Redis, or similar distributed data stores. Hands-on use of frontier-model SDKs (Anthropic, OpenAI, or similar) and AI-assisted development tools, with a realistic view of their…