Director, AI Alignment and Interpretability (Remote)

About the role

Security-domain AI creates alignment and interpretability challenges without good answers in the existing literature. A model trained on offensive techniques, vulnerability research, and proprietary threat telemetry develops internal representations that matter in ways general-purpose models do not. Understanding what that model knows, how it represents threat concepts, and where its behavior could diverge from intent is the research this role exists to do. Most of it hasn't been figured out yet. In this role, you'll lead alignment and interpretability research for CrowdStrike's security-domain AI systems. You'll build methods for reading model internals: identifying features and representations tied to offensive security concepts, detecting misuse signal, and closing the gap between what a model is trained to do and what it actually does. You'll translate those findings into training interventions, behavioral constraints, and evaluation protocols that give the team real confidence in how these models behave. This is hands-on research leadership. The team is lean and the problem space is novel. The right candidate has deep grounding in mechanistic interpretability or a closely related field, clear instincts about what questions matter in a security context, and the ability to advance the state of the art in a space the field is still forming.

Responsibilities

• Contribute original research through publications and external engagement. Interpretability for security-specialized models is understudied. Publishing this work is part of the job.
• Recruit, develop, and retain a lean team of research scientists. Set a technical bar through your own contributions, not just your expectations.

Requirements

• MS or PhD in machine learning, computer science, or a related field, with research depth in interpretability, AI alignment, or a closely adjacent area.
• 8+ years in ML research or engineering, with direct experience doing interpretability or alignment research on large language models.
• Hands-on expertise with mechanistic interpretability methods (probing classifiers, circuit analysis, activation patching, causal tracing, feature visualization) applied to real models. You've done this work, not just reviewed it.
• Experience designing and running alignment evaluations: behavioral testing, capability elicitation, red-lining, or similar methodologies rigorous enough to support meaningful safety claims.
• Track record of leading and growing researchers while remaining an active technical contributor yourself.
• Ways to Stand Out:
• Background in offensive security, vulnerability research, or adversarial ML, with enough depth to recognize what you find in model internals and reason about misuse potential.
• Published research in mechanistic interpretability, AI alignment, or AI safety.
• Experience applying interpretability methods to domain-specialized or fine-tuned models, not only general-purpose foundation models.
• Familiarity

Additional Information

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. 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 also a mission-driven company. We cultivate a culture that gives every CrowdStriker both the flexibility and autonomy to own their careers. 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.

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