Rubrik
Enterprise · Data security & backup
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.
Enterprise · Data security & backup
Currently tracking 7 active AI roles, down 38% 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 |
|---|---|---|
| Senior Machine Learning Engineer Rubrik is seeking a Senior Machine Learning Engineer to join their SAGE team, focusing on building and productionizing "LLM-as-judge" systems for real-time AI agent governance and remediation. The role involves end-to-end model lifecycle management, including data curation, training small models, serving them at production latency, and closing the feedback loop with customer signals. The team emphasizes shipping models to enterprise customers quickly and proving the efficacy of small, specialized models over larger frontier models for AI safety and governance. | Post-trainServe | 9 |