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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. 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 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 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 vLLM, SGLang or Ray. Understanding of MLOps principles and practices. Experience with managing and tuning databases (SQL or NoSQL) and caching systems (Redis, Memcached). Base Salary Range: Base Pay Range $144,000 — $189,000 USD 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.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.