Project Manager, AI Model Enablement and Agentic SDLC

Location:

United States

As a global leader in cybersecurity, Crowd Strike 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 Crowd Strike 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. Crowd Strikers 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 Crowd Strikers 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.

Crowd Strike is a fast-growing cybersecurity company that protects customers from breaches. We are investing in project managers who are energetic, curious, and flexible, and who can run large, complex, cross-functional programs in a fast-paced environment. As a Tech Ops AI Project Manager, you will drive the initiatives that bring AI models and agentic development practices into how our technology organization builds, ships, and operates software.

You will work across Engineering, Security, Data Science, Legal, and IT to make dependencies visible, surface critical issues early, and drive them to resolution.

• Project Leadership: Lead end-to-end execution of Tech Ops AI initiatives. These include onboarding and enabling AI models, coding assistants, and agent platforms, and rolling out agentic workflows across the SDLC (design, coding, code review, testing, release, and operations). Identify, track, and escape critical issues until they are resolved.
• AI Enablement Program Management: Plan and coordinate model access, evaluation, and approval processes. This covers vendor and model onboarding, security and privacy reviews, usage policies, cost and capacity management, and tooling integration. Track adoption and outcome metrics such as usage, developer productivity, quality, and cost.
• Communication and Coordination: Align cross-functional teams and act as the bridge between technical and non-technical stakeholders. Translate fast-moving AI developments into clear plans, risks, and decisions. Own status reporting and communication for small to mid-size projects, and break down silos between engineering, security, and platform teams.
• Change Management and Adoption: Drive adoption of new AI-assisted and agentic ways of working. This means building champion networks, training and communication plans, feedback loops, and playbooks that help engineers adopt these tools with confidence and appropriate guardrails.
• Process Improvement: Thrive in an evolving, growing team and iterate often. Look for ways to improve program management processes, including applying AI and agents to PMO work such as planning, reporting, risk tracking, and dependency management.
• Stakeholder Engagement: Build strong relationships with internal teams and external partners, including AI model providers and tooling vendors. Provide regular, honest updates on progress, risks, and outcomes.

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