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SambaNova Systems

Cloud Platform Architect

SambaNova Systems is hiring a Cloud Platform Architect in Bengaluru, India. Level rates it ; you can apply on SambaNova Systems.

Level's read on this job

  • On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
  • Level classes it as a senior role.
  • SambaNova Systems has 72 other open roles on Level.

AI in this 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

The Cloud Operations team is seeking an experienced engineering leader to scale the platform our internal and external customers use to access SambaNova RDUs.

Responsibilities

In this role, you'll architecting our next-generation system from the ground up, running the Kubernetes infrastructure that powers some of the most advanced AI workloads in the industry, and bridging multi-cloud and on-prem environments in ways no generic SaaS company can offer. Your work will directly impact the productivity of every engineer at SambaNova and by extension, the speed at which we ship the future of AI computing.

Some of your responsibilities include:

  • Architect, build, and maintain our next-generation internal developer platform, automating and streamlining our cloud and on-prem infrastructure
  • Design, write, and manage Terraform modules to provision and manage resources across AWS, GCP, and Azure, ensuring consistency and reproducibility
  • Build and manage highly available, secure, and performant Kubernetes clusters that serve as the primary runtime for our diverse AI workloads
  • Design and implement robust networking solutions (VPCs, load balancers, firewalls, service meshes) that seamlessly connect our multi-cloud and hybrid environments
  • Collaborate with AI and software engineering teams to understand their needs, provide golden paths to production, and build internal tools that accelerate their development cycles
  • Implement best practices for observability (monitoring, logging, tracing) to ensure system reliability and performance, and participate in on-call rotation

Required Qualifications

  • 7+ years of experience in DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles
  • Proficiency in at least one programming language (e.g., Python, Go, Rust)
  • Expertise with Kubernetes (EKS, GKE, or self-managed) in production environments - pods, operators, CRDs, CNIs, etc.
  • Expertise with Infrastructure as Code with the ability to manage complex, multi-cloud environments
  • Strong proficiency with at least one major cloud provider (AWS, GCP, or Azure), with a solid understanding of the core services (compute, storage, networking, IAM)
  • Networking fundamentals (TCP/IP, DNS, HTTP, load balancing) and security best practices in the cloud

Preferred Qualifications

  • Experience in a hybrid environment bridging cloud and on-premise/data center infrastructure
  • Experience managing infrastructure for data-intensive or ML/AI workloads
  • Knowledge of building and maintaining CI/CD pipelines (e.g., GitLab CI, Jenkins, ArgoCD)
  • Experience with service mesh technologies (e.g., Istio, Linkerd)
  • Contributions to open-source projects or a public portfolio of code (GitHub)

Base Salary Range:

Base Pay Range₹10,300,000—₹12,500,000 INR

Submission Guidelines
Please note that in order to be considered an applicant for any position at SambaNova Systems, you must submit an application form for each position for which you believe you are qualified.

EEO Policy
SambaNova Systems is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.

Benefits Summary for US-Based, Full-Time Employment Positions
SambaNova offers a competitive total rewards package, including the base salary, plus equity and benefits. We cover 95% premium coverage for employee medical insurance, and 77% premium coverage for dependents and offer a Health Savings Account (HSA) with employer contribution. We also offer Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life, and AD&D insurance plans in addition to Flexible Spending Account (FSA) options like Health Care, Limited Purpose, and Dependent Care. Our library of well-being benefits available to you and your dependents includes a full subscription to Headspace, Gympass+ membership with access to physical gyms, One Medical membership, counseling services with an Employee Assistance Program, and much more.

How we rate this

Cloud Platform Architect at SambaNova Systems rates 14 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

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