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Cncf Jobs (NOW HIRING)

The Pennsylvania State University

Cloud Native Computing Foundation (CNCF) technology integrations (K8, K3, Rancher, Longhorn, Keycloak, Kyverno) * Infrastructure as Code tools (Ansible, Puppet, Terraform, CloudFormation) * CI/CD ...

Diagrid, Inc

Developer Advocate

San Francisco, CA · On-site +1

Dapr has now achieved graduated status within the CNCF, joining renowned projects like Kubernetes, Prometheus, and Istio. We are backed by top VC firms and supported with industry leading investors ...

Akamai

NY · On-site

$100 - $150/hr

Hold professional certifications from AWS, GCP, Azure, Oracle, and/or CNCF. * Have experience troubleshooting distributed cloud‑native applications and debugging skills across infrastructure ...

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What are the key skills and qualifications needed to thrive in the CNCF position, and why are they important?

To thrive in a CNCF (Cloud Native Computing Foundation) Engineer or Specialist role, you need a strong background in cloud-native technologies, container orchestration, and software development, often supported by a degree in computer science or a related field. Familiarity with Kubernetes, Docker, Helm, and certifications like CKA (Certified Kubernetes Administrator) or CKAD (Certified Kubernetes Application Developer) are highly valuable. Excellent problem-solving, teamwork, and communication skills help you stand out when collaborating on complex cloud-native projects. These abilities are crucial to effectively design, deploy, and manage scalable, reliable cloud infrastructures in fast-paced, collaborative environments.

What are some typical challenges faced by CNCF engineers, and how can they successfully overcome them?

CNCF engineers often encounter challenges such as scaling distributed systems, ensuring security in dynamic environments, and keeping up with the rapidly evolving ecosystem of cloud-native tools. To address these obstacles, successful engineers prioritize continuous learning, leverage automation for efficiency, and actively participate in knowledge sharing within their teams and communities. Collaboration with DevOps teams, developers, and IT security professionals is crucial for building robust solutions. Adapting to new technologies and embracing open-source best practices also helps CNCF engineers remain effective and competitive in their roles.

What is a CNCF?

A CNCF job typically refers to a role related to the Cloud Native Computing Foundation (CNCF), which oversees open-source cloud-native technologies like Kubernetes, Prometheus, and Envoy. These jobs can include positions such as cloud engineers, DevOps engineers, site reliability engineers (SREs), and software developers working with containerized applications. Professionals in CNCF-related roles focus on building, managing, and scaling cloud-native infrastructures using tools from the CNCF ecosystem. Employers hiring for these roles often seek expertise in Kubernetes, cloud platforms, and CI/CD pipelines.

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Infographic showing various Cncf job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 67% Physical, 6% Hybrid, and 27% Remote job distribution.

Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 12 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years, driven by great technology and amazing people. We're now tapping into the unlimited potential of AI to define the next era of computing, where our GPUs power computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent. As an NVIDIAN, you'll work in a diverse, supportive environment where people are encouraged to do their best work and grow their careers. We offer a preference for hybrid work while remaining open to remote arrangements, giving you flexibility in how you do your best work.
Come join the team and see how you can make a lasting impact on the world. The DGX Cloud organization at NVIDIA brings together cutting-edge hardware and software innovation to deliver industry-leading accelerated computing for the world's most ambitious AI workloads. We are a group of forward-thinking engineers tackling some of the globe's toughest challenges, pushing progress, and positively affecting millions of lives. We're searching for a Senior Systems Software Engineer with deep expertise in distributed systems, Kubernetes, containers, and systems performance and scalability. The ideal candidate brings broad, hands-on experience across the stack, including GPU operators, device plugins, distributed inference serving, and major cloud platforms. You'll own hard technical problems at large scale and help shape how AI infrastructure runs in production. In this key role, you will focus on scaling AI infrastructure while minimizing total cost of ownership, reducing cost per token and enabling future AI innovation and AI factories. Are you ready to be impactful?
What you'll be doing:
  • Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack (control and data planes), including NVIDIA components such as GPU Operator, Network Operator, node-feature-discovery, topograph, dra-driver-nvidia-gpu, and nvsentinel, tracking issues from orchestration down to the metal.
  • Design and contribute upstream architectural changes to the Kubernetes control plane and related projects to enable reliable operation at hyperscale cluster sizes, doing in the open what today's hyperscalers typically do privately.
  • Improve container startup and cold-start latency to enable smooth, low-latency inference scaling on Kubernetes across thousands of GPU nodes, ensuring the AI runtime stack scales without creating API server pressure or operational fragility.
  • Assess, improve, and contribute to open-source projects that make Kubernetes an outstanding platform for AI workloads (for example, Grove and gateway-api-inference-extension), composing their architectures with scalability, resilience, and multi-node training/inference in mind.
  • Advance scalability and performance of confidential containers (CoCo) on Kubernetes so encrypted inference workloads meet stringent efficiency and latency requirements in production.
  • Use DSX and related large-scale simulation infrastructure to model full AI-factory deployments and validate scalability across thousands of simulated GPUs, catching failures that emerge only at scale before hardware arrives.
  • Collaborate with AI researchers, developers, customers, and upstream communities to design automated, at-scale workload tests (including replay of production agent traces), build monitoring/analysis tooling, and integrate continuous performance and scale testing into modern CI/CD workflows.
  • Document methods and results clearly and present findings internally and at industry events (for example, KubeCon, GTC), while actively engaging with upstream groups (Kubernetes SIG Scalability, CNCF, and NVIDIA OSS communities) to influence and validate AI workload performance and scalability directions.

What we need to see:
  • Bachelor's or Master's degree in Engineering or equivalent experience, ideally in Electrical, Computer Engineering, or Computer Science
  • 5+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms
  • Expertise in Kubernetes and familiarity with the broader CNCF ecosystem
  • Deep experience with large-scale, parallel, distributed accelerator systems and performance optimization of AI workloads
  • Experience with performance modeling and benchmarking for large-scale systems
  • Proficiency in Golang and/or Python
  • Strong familiarity with the NVIDIA software stack across training and inference
  • Expertise with at least one major public cloud provider (for example, AWS, Azure, GCP, or OCI)

Ways to stand out from the crowd:
  • Strong operational experience with any one of the Kubernetes distributions
  • Prior experience scaling Kubernetes clusters to ultra-large node and object counts
  • Demonstrated history of working in the open-source community
  • Excellent communication and interpersonal abilities
  • PhD or equivalent experience in relevant areas

#LI-Remote
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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