Software Engineer - Agent Cloud

We're building Rubrik Agent Cloud, the enterprise platform to monitor, govern, and remediate AI agents. Our team operates at the intersection of AI, distributed systems, and enterprise security, creating solutions that make it possible for organizations to operate production‑grade AI agents at scale.

As a member of the Rubrik Agent Cloud team, you'll work with cutting‑edge AI technologies while solving complex challenges in scaling, security, and performance. We're a collaborative team passionate about pushing the boundaries of what's possible with enterprise AI infrastructure.

• Design and implement distributed systems that connect the dots between AI agents, identities, and data — giving enterprises real‑time visibility into what agents can access and what they’re doing.
• Build governance and security frameworks that detect and prevent risky agent behaviors.
• Develop the infrastructure that powers “agent observability” — streaming telemetry, audit trails, and behavioral analytics across thousands of agents.
• Architect and scale systems that handle millions of agent decisions per day with low latency and high reliability.
• Design and operate real‑time enforcement systems that make it possible to safely deploy AI agents in enterprise environments.
• Create intelligent feedback and evaluation systems to continuously assess and improve agent trustworthiness.

Innovate at the intersection of AI, security, and distributed systems:

• Design scalable mechanisms for agent discovery and classification
  .
• Contribute to the design of secure, high‑performance cloud infrastructure for agent governance and orchestration.
• Collaborate with AI researchers, security engineers, and platform architects to push the boundaries of what’s possible in enterprise‑grade AI infrastructure
  .

You are passionate about building secure, scalable AI infrastructure that enables enterprises to safely harness the power of intelligent agents.

• BS/MS/PhD in Computer Science or related field — with a strong foundation in systems, distributed computing, or security.
• Experience building large‑scale distributed systems — especially those that process real‑time data, enforce policies, or govern access at scale.
• Background in AI or agentic systems — familiarity with frameworks like Lang Chain, Auto Gen, or CrewAI
  , and a deep understanding of how agents orchestrate tools and APIs.
• Proficiency in cloud‑native architectures — including container orchestration (Kubernetes), microservices, and modern observability stacks.
• Knowledge of enterprise identity, access, and security systems — e.g.,
  Okta, Entra, OAuth, MDMs, EDRs, and data governance platforms
  .
• Experience with modern AI and LLM infrastructure — including model gateways (like LiteLLM or MCP), fine‑tuning, inference optimization, or policy enforcement in AI workloads.
• Strong programming skills in languages like Go, Python, or Java
  , and familiarity with designing APIs and distributed data pipelines.
• Interest in AI governance, risk, and compliance — and curiosity about how to make AI agents safe, observable, and trustworthy in real‑world enterprise environments.

Desire to push boundaries — staying current with the latest research in agent safety, access control, and AI infrastructure design.

$152,400 — $228,700 USD

Rubrik (RBRK), the Security and AI company, operates at the intersection of data protection, cyber resilience and enterprise AI acceleration. The Rubrik Security Cloud platform is designed to deliver robust cyber resilience and recovery including identity resilience to ensure continuous business operations, all on top of secure metadata and data lake. Rubrik’s offerings also include Predibase to help further secure and deploy GenAI while delivering exceptional accuracy and efficiency for agentic applications.

At Rubrik, we are dedicated to fostering a culture where people from all backgrounds are valued, feel they belong, and believe they can succeed. Our commitment to inclusion is at the heart of our mission to secure the world’s data.

Our…