Cloud Engineer III, Falcon Exposure Management (Hybrid

Join Crowd Strike's Falcon Exposure Management Team

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.

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.

Join our Falcon Exposure Management team as one of the first engineers on a new, greenfield initiative. You'll help design and build a product from the ground up, shaping its architecture and its direction.

This is a problem where AI changes what's achievable. It 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.

A security background isn't required. What matters is strong systems engineering, experience running AI-based systems in production, and the curiosity to get up to speed in a new domain quickly.

• Design and build a new product from the ground up, making foundational architecture and technology decisions
• Build the distributed systems foundation: high throughput, large-scale data processing, and the reliability our customers expect
• 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
• Turn open-ended problems into scoped, shippable increments
• Set the technical bar early on quality, testing, and observability, and help grow the engineers around you

• 5+ years of production experience building and maintaining systems at scale
• Strong proficiency in Go, Python, or Java, with solid distributed systems experience — concurrency, partitioning, back pressure, and failure handling under load
• Experience shipping LLM-backed systems to production, including ownership of reliability, cost, and correctness
• Practical experience with agentic loops — designing or operating agents that invoke tools and act on real data, and choosing sensibly among planning, reflection, and multi-step patterns
• A working approach to non-determinism: structured outputs, schema validation, retries, self-checks, and graceful fallbacks
• Strong engineering judgment — the ability to break down an unfamiliar problem, reason about tradeoffs, and choose the simplest approach that works
• Hands-on use of frontier-model SDKs (Anthropic, OpenAI, or similar) and AI-assisted development tools, with a realistic view of their capabilities and limits.
• Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.

• Experience with evaluation and observability tooling for agentic systems
• Experience with RAG pipelines, vector stores, or…