Distinguished Engineer, AI Security Systems

This is a fully remote position, open to applicants in United States.

📋 Description

• Design the Lab’s AI security systems from start to finish, encompassing models, agents, security telemetry, tools, execution environments, on-sensor inference, and cloud-scale reasoning.

• Implement cutting-edge AI at the endpoint using techniques such as distillation, quantization, compact and specialized models, along with integration of kernel- and user-mode telemetry.

• Develop cloud-scale streaming detection and inference systems capable of processing trillions of events daily, with GPU-efficient serving, intelligent model routing, and careful management of cost, latency, and reliability.

• Construct autonomous defenders that conduct investigations, hunt for threats, create and validate detections, and manage response and remediation efforts.

• Design systems that adapt and learn from investigations, adversary emulations, simulations, expert feedback, reinforcement learning, post-training, reward modeling, and synthetic data.

• Engineer solutions to handle adversarial conditions, including evasion, poisoning, prompt injection, tool misuse, sandboxed execution, and autonomous action in customer environments.

• Create benchmarks, cyber ranges, and evaluation frameworks that assess efficacy, false-positive costs, reliability, latency, and expenditures.

• Provide leadership through technical expertise by tackling the most complex challenges, mentoring principal-level engineers and research scientists, and coordinating cross-functional teams.

• Transform research into practical applications within the Falcon platform, addressing scalability, safety, and operational challenges for customer-grade functionalities.

• Represent CrowdStrike through various publications, open-source contributions, standards development, and collaboration with leading AI labs, universities, and the security research community.

⛳️ Requirements

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Applied Mathematics, or a related technical discipline; PhD preferred.

• Over 15 years of industry experience in software engineering, machine learning, or security engineering; 12+ years with a PhD.

• At least 8 years in a senior technical leadership position, such as Principal, Distinguished, or an equivalent role.

• Proven experience in architecting, building, and deploying production AI or ML systems for security, whether at the endpoint or on a cloud scale.

• Practical expertise with large language models and agentic architectures, including planning, tool utilization, memory management, context handling, post-training, reward modeling, and inference optimization.

• Extensive security knowledge in detection and response, threat hunting, malware analysis, vulnerability research, adversary tactics, or security automation.

• Advanced proficiency in one or more programming languages such as C, C++, Rust, Go, or Python.

• Significant experience with distributed systems, high-throughput data infrastructures, and GPU inference stacks such as vLLM, TensorRT-LLM, Triton, or SGLang.

• Strong scientific rigor with the capability to formulate hypotheses, establish credible baselines, design impactful experiments, and follow the evidence.

• Track record of setting a technical vision, elevating standards for senior engineers and researchers, and clearly communicating complex trade-offs.

• Demonstrated success in leveraging AI technologies to enhance decision-making, streamline workflows and processes, boost efficiency, and achieve business goals.

• Cybersecurity experience spanning endpoint, cloud, identity, SIEM, or threat intelligence domains.

• Background in a frontier AI lab focusing on pre-training, post-training, reinforcement learning, inference, evaluation, or safety.

• Experience with adversarial machine learning, AI red teaming, autonomous cyber reasoning systems, or AI-driven offensive security.

• Expertise in creating extensible AI or agentic platforms that allow teams to safely develop, assess, optimize, and deploy AI applications at scale.

• Recognized technical contributions, including publications, patents, notable open-source projects, or conference presentations in the fields of AI and security.

🏝️ Benefits

• Competitive compensation and equity awards.

• Comprehensive wellness programs covering both physical and mental health.

• Generous vacation and holiday policies to ensure proper rest and recharge.

• Paid parental and adoption leave.

• Opportunities for professional development accessible to all employees, irrespective of their level or role.

• Employee networks, geographic neighborhood groups, and volunteer initiatives to foster connections.

• Health insurance coverage.

• 401k plan.

• Paid time off.

• Performance bonuses.

• Equity grants.