Jobs / United States / Sambanova Systems INC
Principal Cloud Platform Engineer
Sambanova Systems INC · 🇺🇸 Austin, Texas, United States; San Jose, California, United States
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 23 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 4 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Sambanova Systems INC paid sponsored hires in similar roles8 certified filings for “Principal Engineer” (Computer and Information Research Scientists) in CA: $175k–$190k, median $183k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Sponsor Radar — Sambanova Systems INC
The US Department of Labor certified 23 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 4 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Sambanova Systems INC →
About the role
SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value. 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. Responsibilities Some of your responsibilities will include: • 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 Required Qualifications • B.S. in Computer Science, Computer Engineering, or related field • 5+ 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 Preferred Qualifications • 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 v