Principal Cloud Platform Engineer
About The Position
The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale. SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets. 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 Principal Cloud Platform Engineer, you will be specializing in our AI Inferencing Service and will be the guardian of its reliability, performance, and scalability. You will bridge the gap between software development and operations, applying an engineering mindset to solve operational challenges. Your primary focus will be ensuring our inference endpoints have exceptional uptime, low-latency response times, and efficient resource utilization, directly impacting the experience of our customers and the success of our AI products. This role includes participating in a shared on-call rotation to maintain 24/7 service reliability.
Requirements
- B.S. in Computer Science, Computer Engineering, or related field
- 3+ years of experience in a Site Reliability Engineering, DevOps
- Experience supporting a large-scale, customer-facing service in a public cloud environment (AWS, GCP, Azure)
- Strong programming and scripting skills in languages like Python, Go, Rust, or Java
- Proven experience with containerization and orchestration technologies (Docker and Kubernetes)
- Deep understanding of monitoring and observability principles and tools (e.g., Prometheus, Grafana, ELK Stack, Datadog)
- Experience with Infrastructure as Code (e.g., Terraform, CloudFormation)
- Experience with CI/CD principles and tools (e.g., Jenkins, GitHub Actions, ArgoCD)
- Strong Linux/Unix system administration fundamentals
Nice To Haves
- Experience in a hybrid environment bridging cloud and on-premise/data center infrastructure.
- Direct experience supporting ML/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 like vLLM, SGLang or Ray.
- Understanding of MLOps principles and practices.
- Experience with managing and tuning databases (SQL or NoSQL) and caching systems (Redis, Memcached).
Responsibilities
- Shared ownership of the production inferencing service across regions, covering availability, latency, performance, change management, and capacity planning
- Standing-up and automating AI infrastructure in new regions
- Participating in a shared primary/secondary on-call rotation, and leading incident response
- Building monitoring, alerting, and dashboards in Prometheus, Grafana, and Datadog for service health, model latency and throughput, and accelerator utilization
- Finding and eliminating performance bottlenecks
- Designing auto-scaling policies that handle variable inference loads
- Managing cloud and on-prem infrastructure as code in Terraform and Ansible
- Building CI/CD pipelines that safely deploy new model versions and service updates
- Forecasting infrastructure needs against the product roadmap and usage trends, and working with finance to manage cloud spend
- Defining and reporting on SLOs and SLIs for the inferencing platform, using that data to prioritize reliability work
Benefits
- Equity
- 95% premium coverage for employee medical insurance
- 77% premium coverage for dependents
- Health Savings Account (HSA) with employer contribution
- Dental insurance
- Vision insurance
- Short/Long term Disability insurance
- Basic Life insurance
- Voluntary Life insurance
- AD&D insurance
- Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care
- Full subscription to Headspace
- Gympass+ membership with access to physical gyms
- One Medical membership
- Counseling services with an Employee Assistance Program
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What This Job Offers
Job Type
Full-time
Career Level
Principal
