Jobs at CrowdStrike

Lead design and delivery of large-scale AI/ML and retrieval systems for cybersecurity. Build end-to-end ML architecture, models (anomaly detection, ranking, RAG/LLM), and production infrastructure. Drive technical strategy, cross-functional initiatives, experimentation, and mentor junior scientists while balancing latency, scalability, reliability, and business impact.

Manage customer onboarding, training, adoption, retention, and growth for the Falcon Shield SaaS security platform. Build trusted relationships with security teams, understand business objectives, create measurable success plans, conduct strategic reviews, demonstrate product value, and advise on SaaS security posture and architecture. Collaborate with Product and R&D teams on customer feedback and feature improvements while using AI technologies to improve workflows and decision-making.

Analyzes the exposure management competitive landscape, synthesizes technical and market intelligence, conducts win/loss analysis, supports competitive deals, develops field enablement materials, and recommends product and go-to-market strategies. Partners with Product, Sales, Marketing, Strategy, Investor Relations, and senior leadership to translate complex cybersecurity concepts into actionable guidance and executive insights.

Drive new business and expand enterprise accounts by positioning CrowdStrike as the preferred cybersecurity supplier. Build and maintain C-level relationships, develop account plans, lead virtual teams, manage pipeline and forecasts, and close large solutions. Collaborate with internal teams to deliver tailored proposals and consistently meet or exceed individual sales quotas.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Detect, contain, and remediate security incidents across Windows, macOS, and Linux. Perform malware and forensic analysis, develop detection and remediation processes, produce customer-facing reports and recommendations, and contribute to public thought leadership. Use scripting/programming and AI tools to enhance investigations and response.

Design, build, and deploy production LLM-based agents from prototype to production. Lead prompt engineering, fine-tuning (LoRA/QLoRA), performance optimization, and scalable, secure deployments. Collaborate cross-functionally to integrate agents into enterprise workflows and ensure AI safety and responsible development.