Senior Systems Software Engineer, Developer Productivity and Cloud Automation - GeForce NOW

Posted 8 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
184K-357K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build and maintain a Kubernetes-native deployment and automation platform: backend microservices and APIs, GitOps pipelines, CRDs/operators in Go, multi-cloud and bare-metal automation with Terraform/Ansible/Vault, staging/prod-like environments, monitoring and SLOs, and integrations with CI/CD, observability, and automated remediation to enable zero-downtime global rollouts.
Summary Generated by Built In

GeForce NOW is NVIDIA's Cloud Gaming service, streaming games at the highest quality to any and every user, regardless of their device type and capabilities - low-end PCs, Macs, TV or mobile devices. Using the most sophisticated GPUs and NVIDIA proprietary software, GeForce NOW transforms the gaming experience with always up-to-date games on always the latest hardware, a streaming experience rivaling that of a local PC, and near-instant launch – just click and play! For more details, see http://www.geforce.com/geforce-now

Our mission empowers every GeForce NOW engineer to deliver confidently by removing obstacles, catching issues early, and turning deployments into a strength rather than a liability. We handle pipelines using GitLab’s CI platform and Jenkins, along with Flux CD and Argo CD rollouts, StackStorm event-driven automation, HashiCorp Vault for credential storage, and automation across multi-cloud environments.

What You'll Own

This is the Kubernetes-native deployment platform paired with its automation system and the backend services and APIs that support it. We deliver zero-downtime global rollouts with automatic drift detection. Our reliable staging environments replicate production accurately. We provide cloud automation for bare-metal and multi-cloud environments. If a GFN service ships, runs, or self-heals, you build the infrastructure behind it.

What You'll Be Doing:

  • Build and develop backend microservices and REST/gRPC/MCP APIs that power the deployment platform, zone reservation/lease system, and developer self-service tooling

  • Extend the platform with dynamic delivery, automatic rollback, drift detection, and automated zone bootstrapping

  • Build and stabilize prod-like staging environments/zones so teams catch regressions early

  • Develop and sustain GitOps pipelines (Flux CD, Argo CD) across on-premises and Nvidia GFN Cloud/AWS/Azure/GCP

  • Develop Kubernetes CRDs and operators in Go for scheduling, auto-scaling, and compliance across data centers

  • Build backend integrations and control-plane services connecting CI/CD, observability, and automation systems into a unified platform experience

  • Automate dedicated hardware and multiple cloud platform configurations using Terraform, Ansible, and Vault

  • Implement monitoring solutions including Prometheus, Grafana, Datadog, and ELK, paired with SLO/alerting for early detection

  • Integrate automation tools — runbooks, StackStorm bots, anomaly-triggered remediation, and Slack self-service release bots

What We Need to See:

  • Bachelor or higher degree in computer science, engineering, or equivalent experience.

  • 10+ years of experience in Cloud Infrastructure and DevOps, with deep expertise in Kubernetes, GitOps (or equivalent), and production-grade cloud-native CI/CD pipelines

  • Expert Kubernetes: CRDs, operators, multi-cluster management, and security hardening (CIS, PCI/SOC 2)

  • Proficiency in Flux CD or Argo CD, GitLab CI, and Jenkins; Go or Python for control plane development

  • Experience handling Vault, Terraform, Ansible, and Helm in both on-premises and cloud environments

  • Experience in developing and scaling RESTful, gRPC, MCP APIs and backend services.

  • Experience running hybrid multi-cloud and bare-metal at production scale, and owning a platform roadmap end-to-end.

Ways to Stand Out from the crowd:

  • Backstage or similar internal developer portals for self-service tooling

  • Comprehensive expertise covering backend services as well as platform and infrastructure engineering

  • Daily use of AI-assisted tools (Claude Code, GitHub Copilot, Cursor) — we use these daily

  • Hybrid infrastructure spanning on-premises GPU clusters and public cloud

With competitive salaries and a generous benefits package, NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 30, 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.

Skills Required

  • Bachelor or higher degree in computer science, engineering, or equivalent experience.
  • 10+ years of experience in Cloud Infrastructure and DevOps.
  • Expert Kubernetes: CRDs, operators, multi-cluster management, and security hardening (CIS, PCI/SOC 2).
  • Proficiency with GitOps and Flux CD or Argo CD, GitLab CI, and Jenkins.
  • Experience developing control-plane software in Go or Python.
  • Experience handling HashiCorp Vault, Terraform, Ansible, and Helm in on-premises and cloud environments.
  • Experience developing and scaling RESTful, gRPC, MCP APIs and backend services.
  • Experience running hybrid multi-cloud and bare-metal at production scale and owning platform roadmap end-to-end.
  • Experience implementing monitoring solutions (Prometheus, Grafana, Datadog, ELK) and SLO/alerting.
  • Experience with automation/integration tools (StackStorm, runbooks, Slack bots) and CI/CD/observability integration.
  • Backstage or similar internal developer portals for self-service tooling.
  • Comprehensive expertise covering backend services and platform/infrastructure engineering.
  • Daily use of AI-assisted coding tools (Claude Code, GitHub Copilot, Cursor).
  • Experience with hybrid infrastructure spanning on-prem GPU clusters and public cloud.

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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