AI TechOps Project Manager: Enable Models & Agentic SDLC

CrowdStrike Inc.; United States; Remote; USD 85,000 - 120,000; Full time

Benefits offered by this job

Parental leave

Professional development

Employee networks

Wellness programs

Vacation and holidays

Job summary

CrowdStrike is seeking a TechOps AI Project Manager to lead large, cross-functional programs that bring AI models and agentic workflows into how our software is built, shipped, and operated. You will collaborate across Engineering, Security, Data Science, Legal, and IT to surface issues early and drive resolution.

Responsibilities include onboarding and evaluating models, managing access and policies, tracking usage, cost, and productivity, and translating rapid AI developments into clear plans

Qualifications

• 4+ years of program or project management experience in software engineering, technical operations, developer productivity, or platform organizations.
• Experience owning a program or portfolio of products or features with scoping requirements and planning milestones.
• Working knowledge of the modern SDLC (CI/CD, code review, testing, release management) and how AI coding assistants, LLMs, and agents are changing it.
• Familiarity with core AI concepts: model selection and evaluation, prompt and context management, agent frameworks and tool use.

Responsibilities

• Lead end-to-end execution of TechOps AI initiatives, including onboarding AI models, coding assistants, and agent platforms across the SDLC.
• Plan and coordinate model access, evaluation, and approval processes, including vendor onboarding, security reviews, usage policies, cost and capacity management.

Skills

Program management

Cross-functional collaboration

Communication skills

AI/ML understanding

Job description

CrowdStrike is seeking a TechOps AI Project Manager to lead large, cross-functional programs that bring AI models and agentic workflows into how our software is built, shipped, and operated. You will collaborate across Engineering, Security, Data Science, Legal, and IT to surface issues early and drive resolution.

Responsibilities include onboarding and evaluating models, managing access and policies, tracking usage, cost, and productivity, and translating rapid AI developments into clear plans