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Rubrik is hiring a Senior Software Engineer to join the Enterprise AI team, an internal AI enablement engine focused on evaluating where AI can drive real impact, building platforms and patterns for adoption, and helping engineering teams work smarter and faster.
You will design, build, and operate the platform and backend systems that power Rubrik at scale. This is a hands-on, high-ownership role where you write production code, design systems, lead code reviews, and make the engineering organization more effective. You'll own core infrastructure spanning Kubernetes and cloud-native services to APIs and developer tooling, working closely with product, AI, and security teams.
Key responsibilities include:
- Own end-to-end delivery of major platform initiatives from design through deployment and post-launch success
- Own Kubernetes at depth—clusters, networking, operators, container lifecycle, and multi-tenant orchestration
- Design, develop, and optimize distributed services and cloud-native infrastructure on AWS and/or GCP for scale, reliability, and performance
- Drive engineering excellence through code quality standards, design reviews, automation, and CI/CD best practices
- Collaborate across Product, AI, and Security teams to align architecture with business objectives
- Mentor and guide engineers through architecture decisions, trade-offs, and delivery
- Partner with leadership to align engineering strategy with product objectives and technical roadmap
Rubrik's mission is to secure the world's data. The company operates at the intersection of data protection, cyber resilience, and enterprise AI acceleration, with products including Rubrik Security Cloud and Rubrik Agent Cloud for monitoring and auditing agentic actions.
REQUIREMENTS:
Required:
- 9+ years of software engineering with deep backend and infrastructure focus
- Strong programming skills in Python and/or Go—you ship production code, not just scripts and configs
- Deep, hands-on Kubernetes experience—building and operating clusters, not just deploying to them
- Proven experience designing and operating distributed systems in production
- Cloud-native fluency across AWS and/or GCP—compute, storage, IAM, networking, and managed services
- Experience with infrastructure-as-code (Terraform or similar) and CI/CD pipelines
- Familiarity with applied AI tooling and patterns—agentic AI tools (Claude, LiteLLM), AI gateways, agent frameworks—and ability to build backend services that integrate with them
- Strong system design and architectural judgment
- Clear communicator who partners well across product, security, and AI teams
Preferred:
- Observability stacks—Prometheus, Grafana, Datadog, OpenTelemetry
- Multi-cloud or hybrid infrastructure experience (AWS, GCP, on-prem)
- Familiarity with API gateways, AI gateways, and policy/authorization frameworks (ABAC, OPA)
- Service mesh or platform-as-a-service design experience
- Track record of improving engineering productivity at scale
