Software Detection Engineer - Cloud, Identity Protection (Hybrid, ISR)

As a global leader in cybersecurity, CrowdStrike 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 CrowdStrike 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. CrowdStrikers 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 CrowdStrikers 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.

About

the Role: You will build globally distributed, fault-tolerant, and highly scalable identity threat detection systems that analyze billions of authentication events per day to detect sophisticated Active Directory attacks, credential theft, and lateral movement across hybrid and multi-cloud (Azure/Entra, Okta, AWS) environments. You'll design, lead, and implement the next generation of CrowdStrike's Identity Protection detection platform — evolving it from on-prem appliances toward cloud-native, event-streaming microservices.

What You'll Do Design and implement real-time detection rules and pipelines over high-throughput Kafka event streams, maintaining sub-second detection latency at massive scale. Build the pluggable detection engine and rule framework that turns raw authentication telemetry into indicators, and indicators into enriched, customer-facing alerts. Develop machine-learning and behavioral-anomaly models, and integrate LLM-based detection reasoning (e.g. AI-driven severity scoring) into production detection flows. Translate security research into production-grade detections, partnering with security researchers who guide you on the threat landscape. Own detections in production: observability, latency SLOs, safe per-customer rollouts (feature-flag-gated), and incident response for the detection pipeline. Work across a polyglot stack — Python for detection logic and ML, Go for the high-performance streaming services, Java for backend alert management. Tech Stack: Python · Go · Java · Kafka · PostgreSQL · MongoDB · Redis · Protobuf/gRPC · GraphQL · AWS · LogScale/NG-SIEM · LLM / GenAI tooling What You'll Need: Programming mastery in Python with deep expertise in data structures, algorithms, and distributed systems (Go experience a strong plus — it's core to our next-gen services). 6+ years building backend / distributed systems at scale. Hands-on experience with event-streaming / message-queue architectures (Kafka or similar) and distributed data processing. Experience with relational and document stores (PostgreSQL, MongoDB) and caching (Redis). BS or MS in Computer Science or related engineering discipline.