Senior Software Engineer - Enterprise AI

The Enterprise AI team is Rubrik’s internal AI enablement engine. We evaluate where AI can make a real difference, build the platforms and patterns that make adoption easy, and help engineering teams across the organization work smarter and faster. We operate at the intersection of applied AI, distributed systems, and enterprise operations, with the primary mission of making Rubrik more efficient through AI-powered workflows.

This is a high-impact, high-autonomy team where you will work closely with engineering, product, and operations teams across Rubrik to bring AI capabilities to life.

We are hiring a Senior Software Developer to design, build, and operate the platform and backend systems that power Rubrik at scale. You will own core infrastructure, spanning Kubernetes, cloud-native services, APIs, and developer tooling. Working closely with product, AI, and security teams, this is a hands-on, high-ownership role where you write production code, design systems, lead code reviews, and raise the bar for the entire engineering organization.

• 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 teams — Product, AI, and Security — to align architecture with business objectives.
• Be a mentor and multiplier, guiding engineers through architecture decisions, trade-offs, and delivery.
• Partner with leadership to align engineering strategy with product objectives and technical roadmap.

• 7+ years of professional software engineering experience in backend and infrastructure development, with a proven record of delivering and running production systems.
• Strong hands-on coding in C++, Go, or Java, plus working fluency in Python, with production code beyond scripts and configs.
• Solid grounding in data structures, algorithms, concurrency, and memory management.
• Someone who has built applied AI tooling (e.g., Claude, LiteLLM, AI gateways, agent frameworks) and the ability to build backend services that integrate with them.
• Experience designing distributed systems (consistency, replication, fault tolerance, scalability), with strong system design and architectural judgment.
• Familiarity with storage and database systems (SQL, NoSQL, key-value, file/object storage).
• Experience building and operating container clusters (Docker, Kubernetes), not just deploying to them.
• Cloud-native fluency on AWS or GCP (compute, storage, IAM, networking, managed services).
• Hands-on infrastructure-as-code (e.g., Terraform) and CI/CD pipelines.
• Strong debugging, profiling, and performance-tuning skills.
• Clear written and verbal communication, including design docs, and effective partnership across product, security, and AI teams.

• 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.