Jobs at CrowdStrike

Develop and own core features for CrowdStrike’s Windows endpoint security sensor across operating-system subsystems, including filesystems, memory, processes, and networking. Collaborate across distributed sensor teams on architecture, cross-platform delivery, and strategic initiatives. Lead features through design, implementation, demonstrations, and release while mentoring engineers. Diagnose memory corruption, process contention, and performance issues, and apply AI technologies to improve workflows and decision-making.

Lead the design and implementation of cloud architecture components and deliver low-latency, highly scalable services. Collaborate with desktop agent and AI teams, drive technical decisions across stakeholders, and improve engineering practices through hiring, design reviews, postmortems, code reviews, and mentorship. Apply AI technologies to improve decision-making, workflows, efficiency, and business outcomes while operating resilient, high-volume Tier-1 cloud systems.

Lead the design and implementation of major cloud architecture components and deliver low-latency, highly scalable services. Collaborate with desktop agent and AI teams, drive technical decisions across stakeholders, and improve engineering practices through design reviews, postmortems, hiring, code reviews, and mentorship. Apply AI technologies to improve decision-making, workflows, efficiency, and business outcomes while operating high-volume, resilient Tier-1 cloud systems.

Research and implement macOS detection techniques and build them into production endpoint sensor features. Drive projects from concept through release, collaborate cross-functionally, troubleshoot issues, and apply secure, high-performance engineering practices using Swift/C++ and related tools.

Design and implement Windows sensor detection and prevention features for the Falcon platform. Research attack techniques, develop user- and kernel-mode detection logic, own features from design through release, apply secure coding and CI/CD practices, troubleshoot customer issues, and collaborate across teams to improve telemetry and protections.

Senior backend engineer on the cloud Platform auth team building high-scale authentication and authorization services. Lead design and implementation of distributed systems, APIs, storage, and performance optimizations; mentor engineers; apply engineering best practices and AI to improve decision-making and scalability.

Lead product strategy and roadmap for AI-native capabilities in CrowdStrike's Next-Gen SIEM. Collaborate with engineering, data science, research, marketing, sales, and support to design, deliver, and position AI-driven detection, investigation, and prevention features. Conduct competitive analysis, define use cases, and engage customers to inform product direction while supporting go-to-market and cross-functional execution.

Design and implement core features for a lightweight macOS security sensor, collaborate cross-platform with teams, own feature lifecycle from design through delivery, debug low-level memory and performance issues, and mentor distributed engineers while aligning sensor architecture with broader Falcon Host strategy.

The role involves designing and developing core features for the Linux sensor in CrowdStrike's security platform, collaborating with teams across the company, and maintaining software quality for cross-platform delivery.

Lead the design and implementation of cloud architecture to support CrowdStrike's mission in cybersecurity, ensuring scalability and resilience of services.

Lead strategy and execution for CrowdStrike's Identity Protection product: detect and prioritize identity risk across human and non-human identities, define identity graph models, drive remediation automation and verification, and surface identity risk across the security stack. Use AI agents and rapid prototyping to iterate specs and partner with engineering, customers, and stakeholders to deliver usable identity risk solutions.

Research and implement Linux-based detection techniques and production-quality sensor features for endpoint threat detection. Design, develop, test, and deliver high-performance C/C++ code with strong OS internals knowledge, collaborate cross-functionally, and troubleshoot customer issues. Balance research, reverse engineering, and engineering best practices to ship reliable, high-concurrency sensor features.

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.

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.

Creates customer-focused product documentation, including feature documentation, release notes, and API documentation. Researches complex products, collaborates with subject matter experts, designers, engineers, and product managers, and follows structured authoring standards. Advises other writers, manages projects independently, contributes to content strategy, and uses AI to improve documentation workflows and customer experiences. The role requires strong technical writing, audience analysis, user-centered thinking, DITA/XML knowledge, authoring-tool experience, and version-control familiarity.

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.

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.