Vice President, AI Architect (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:

We’re looking for a VP-level AI Architect to define and drive a consistent, modern AI- and agentic-first architecture across CrowdStrike. This company-wide role spans business units, customer-facing products, shared platforms, and internal AI capabilities.

You’ll connect AI applications with the software and infrastructure that make them work at scale. Working with business unit and engineering leaders, you’ll translate business priorities into practical designs, establish common technical foundations, and guide implementation across teams. The architecture must support distinct product needs while making shared capabilities easier to build, integrate, and operate.

Your work will range from company-wide architectural decisions to building reference implementations and resolving difficult engineering problems. You’ll bring deep systems expertise, sound judgment about emerging AI technologies, and a record of turning architectural direction into working products.

What You’ll Do:

• Define and drive the company-wide AI architecture and roadmap. Establish shared interfaces and design patterns, resolve cross-business-unit tradeoffs, and work with product and engineering leaders to put architectural decisions into practice. Determine which capabilities should be common and where teams need flexibility.
• Design and build full-stack AI and agentic systems. Connect models and retrieval to agent runtimes, memory, tools, and execution environments. Develop prototypes and production reference implementations that give teams a tested foundation for new capabilities.
• Architect production AI systems for performance, resilience, and scale. Benchmark model and serving options, investigate bottlenecks across software and infrastructure, and improve latency, throughput, and compute efficiency. Guide deployment choices across cloud and edge environments.
• Create a consistent developer experience across products through reusable components, common APIs, and shared tooling. Simplify integration and establish engineering practices that teams adopt. Contribute to critical implementations, review designs and code, and mentor engineers and technical leaders.
• Design the AI lifecycle architecture, from data ingestion and model adaptation through evaluation, deployment, and operational feedback. Establish reproducible workflows, automated quality gates, and observability for model quality, agent task success, reliability, and cost. Build safe rollout, rollback, and recovery into production systems.
• Embed security, governance, and auditability into AI architectures. Define permissions and execution boundaries for agents, address prompt injection and data exposure, and make system actions traceable. Partner with Security and Legal to translate requirements into practical engineering controls.

What You’ll Need:

• BS, MS, or PhD in computer science, computer engineering, or a related technical field, or equivalent practical experience.
• 10+ years of experience in software architecture, systems engineering, or AI engineering, including senior technical leadership across multiple products or business units.
• A record of personally desi…