Senior Principal Cloud Platform Engineer

Location: Bengaluru, Karnataka, India

Department: Software

About the team

The Cloud Platform team owns the production inferencing service that serves SambaNova's models to customers on RDU accelerators, including capacity planning, deployment, monitoring, and incident response across regions in the United States, Asia, Europe, and Latin America.

About the team

The Cloud Platform team owns the production inferencing service that serves SambaNova’s models to customers on RDU accelerators, including capacity planning, deployment, monitoring, and incident response across regions in the United States, Asia, Europe, and Latin America.

About the role

As a Senior Principal Cloud Platform Engineer, you’ll set the technical direction for keeping our AI inferencing platform reliable, fast, and scalable. Your focus is uptime, latency, and resource

utilization on the inference endpoints customers depend on. The work spans monitoring, deployment, capacity planning, and incident response, and includes a shared on-call rotation providing 24/7 coverage. You’ll also serve as a technical leader for the Bengaluru team, mentoring engineers and shaping reliability and platform practices across regions.

Responsibilities

• Own the availability, latency, and efficiency of the production inferencing service,including change management, emergency response, and standing up AI infrastructure in new regions
• Define the reliability and platform engineering strategy for the service, including SLOs, error budgets, and multi-region architecture, and drive alignment with engineering, product, and operations stakeholders
• Build and maintain monitoring, alerting, and dashboards in Prometheus, Grafana, and Datadog covering service health, model latency and throughput, and RDU utilization
• Lead incident response for high-severity events, run blameless post-mortems, and drive systemic fixes and automation of the toil those incidents expose
• Find and fix performance bottlenecks, and design auto-scaling and capacity planning policies that handle variable inference load without overspending
• Manage cloud and on-prem infrastructure as code in Terraform and Ansible, and architect the CI/CD pipelines that deploy new model versions and service updates
• Mentor and raise the technical bar for SRE and platform engineers, through design reviews, on-call practices, and knowledge sharing

Required Qualifications

• B.S. in Computer Science, Computer Engineering, or related field, or equivalent practical experience
• 10+ years of experience across Site Reliability Engineering and Platform Engineering roles supporting large-scale, customer-facing services in public cloud environments (AWS, GCP, Azure)
• Proven track record of technical leadership, including owning the architecture and reliability of production systems and mentoring other engineers
• Strong programming and scripting skills in Python, Go, or Java
• Production experience with Docker and Kubernetes
• Deep understanding of monitoring and observability tooling such as Prometheus, Grafana, Datadog, or the ELK Stack
• Experience with infrastructure as code using Terraform or CloudFormatio 
• Experience with CI/CD tooling such as Jenkins, GitHub Actions, or ArgoCD
• Strong Linux system administration fundamentals

Preferred Qualifications

• Experience in a hybrid environment spanning cloud and on-premise data center infrastructure
• Experience supporting ML or AI inferencing services in production
• Familiarity with GPU-accelerated computing and optimizing workloads for NVIDIA GPUs, for purposes of mapping to RDUs
• Knowledge of model serving frameworks such as vLLM, SGLang, or Ray
• Experience managing and tuning databases (SQL or NoSQL) and caching systems such as Redis or Memcached