Director of Engineering, Sensor Detection Platform (Remote)

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:

CrowdStrike stops breaches, and the sensor is where that fight happens first. The Sensor Detection Platform team builds the on-sensor detection engines (behavioral pattern matching, process classification, and emerging on-sensor inference) that execute detection logic on hundreds of millions of endpoints in real time, along with the infrastructure that lets detection engineers author, test, deploy, and manage that content safely across the entire Falcon fleet.

We are looking for a Director of Engineering to lead this platform. You will manage multiple teams responsible for the sensor-side detection engines and template/pattern frameworks, the process and application classification systems that power features like Application Abuse Prevention and agentic-workload identification, and the supporting infrastructure: content build and channel-file delivery pipelines, feature-flag and staged-rollout controls, pre-release validation and test environments, and the fleet health observability that

keeps detection running reliably on customer endpoints.

This is a high-leverage role at the foundation of CrowdStrike's detection strategy. Every detection the company ships, whether endpoint, identity, or hybrid, ultimately executes through your platform, and every improvement you make translates directly into faster, higher-quality protection for thousands of customers with zero tolerance for endpoint disruption.

What You'll Do:

• Own the multi-year strategy, architecture, and roadmap for on-sensor detection: execution engines, template and pattern frameworks, process classification, and the content delivery infrastructure that supports them
• Lead and grow an organization of managers and senior engineers across multiple teams, owning the full talent lifecycle: hiring, coaching, performance, and succession
• Be accountable for both detection efficacy and endpoint footprint (the CPU, memory, and I/O cost of detection on customer machines), including performance budgets, regression gates, and fleet health SLOs
• Make shipping detection content to the fleet provably safe: pre-release validation, staged channel-file deployment, rollback, exclusion management, and end-to-end testing across OS platforms and sensor versions
• Drive the evolution of on-sensor intelligence, including process classification for AI and agentic workloads and the runtime foundations for on-sensor model inference
• Partner closely with detection content engineering, the core sensor organization, the Cloud Detection Platform, and product management to deliver a coherent hybrid sensor/cloud detection architecture
• Reduce operational drag on the platform: drive down support escalation volume, keep test infrastructure trustworthy, and streamline release operations
• Anticipate and manage escalations and cross-team dependencies, and represent the platform in architecture and planning forums across the product organization
• Drive annual operating plan and organizational planning for your area, and reflect CrowdStrike's culture in how your teams operate

What You'll Need:

10+ years of software engineering experience, including 5+ years managing engineering teams and 2+ years managing managers

Deep endpoint experience: building and operating software that runs on customer endpoints at scale, including EDR/endpoint security agents, OS internals across Windows, macOS, and Linux, and the performance and compatibility discipline that work demands

• Experience safely delivering software and content updates to very large distributed fleets, where a bad push is customer-visible within minutes
• A track record of being fully accountable for strategic outcomes over one-to-two-year horizons, not just project delivery
• Strong architectural judgment: you can engage credibly in design reviews, weigh efficacy-versus-footprint tradeoffs on constrained devices, and make build/buy/consolidate calls
• Experience managing operational excellence for customer-facing systems: incident response, release safety, fleet health monitoring, and escalation management
• Demonstrated ability to lead through ambiguity, including organizational change, competing priorities, and cross-team dependencies
• Excellent communication skills with executives, peers, and engineers

Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes.

Bonus Points:

• Domain experience in detection engineering, malware analysis, or threat intelligence, including adversarial evaluation programs such as MITRE ATT&CK evaluations
• Experience with detection-as-code, content management systems, or rule/template authoring platforms
• Experience with on-device ML: model runtimes, inference on heterogeneous hardware, or resource-constrained deployment of models
• Experience integrating AI-assisted or agentic workflows into engineering practice