Rubrik has 17 active job listings related to artificial intelligence. The majority of these roles, 71%, are focused on agents. The company is primarily hiring for engineering positions, with 11 roles available. Recent hiring activity shows a significant increase, with 10 new AI roles posted in the last 30 days, a 900% rise compared to the previous 30-day period.
Currently tracking 7 active AI roles, up 23% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $135k–$263k (avg $197k).
Rubrik currently has 15 active AI-related roles in our index. The most common open titles are: Application Security Engineer, Cyber Resilience Architect, APJ, Data Science Intern , Data Science Researcher (Part-Time 25%), Enterprise Architect, Global IT. Most positions are in Engineering and Product.
Rubrik's active AI hiring is concentrated in: agents (67%), post-training (13%), application (7%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Rubrik is hiring AI talent in: India (8 roles), United States (4 roles), Israel (3 roles).
Job postings at Rubrik most frequently reference: agent orchestration, guardrails, fine tuning, model serving, inference infra.
In the past 30 days, Rubrik has posted 3 new AI-related roles. That is a -67% change versus the prior 30 days (9 → 3).
| Title | Stage | AI score |
|---|---|---|
| Staff Product Manager, Rubrik Security Cloud AI Platform Staff Product Manager to own the AI Platform that powers the Rubrik Security Cloud control plane. This role involves designing the system for AI agents to make decisions, act safely, and scale, focusing on the infrastructure layer including governance, guardrails, permissions, multi-tool orchestration, failure handling, memory management, and cost containment. | Agent | 7 |
| Senior Product Manager-Data Discovery & Classification Product Manager for Rubrik's Data Discovery & Classification portfolio, focusing on AI-driven security. The role involves defining strategy, customer discovery, and execution for discovering, classifying, and interpreting sensitive data across cloud and on-prem environments. Collaboration with engineering, design, GTM, and Data Science teams is key, particularly on classification engines and LLM-based classifiers. | Data |
| 7 |