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Job Summary 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. 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. 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. Responsibilities 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 Requirements BS or MS in Computer Science or equivalent experience with 12+ 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 Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying. .
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The employers posting the most developer roles are Link Group (369 jobs), Upvanta (257), jobgether (226), and OfferZen (212). If you're applying to any of these, research their hiring patterns. They move fast and post often, which means they're either scaling hard or replacing people who didn't fit.
In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.