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Senior Production Engineer - DGX Cloud

NVIDIA· Engineer, Sys SW
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Hybrid (Remote - Switzerland), Zurichfull-timePosted 2w ago

About the role

Senior Production Engineer to build software and automation for DGX Cloud production services, focusing on reliability, scalability, and safe operation across multi-cloud and on-prem environments.

Responsibilities

  • Build and operate production software, automation, and tooling for control plane services, model deployments, and inference and agentic workloads across DGX Cloud environments.
  • Improve the reliability of inference and agentic platforms and services, including NVIDIA Cloud Functions, SGLang- and vLLM-based endpoints, and inference services built with NVIDIA Dynamo, through health validation, safer rollouts, observability, and recovery.
  • Improve endpoint availability, inference routing, capacity management, and service health to maintain predictable performance as workloads and demand change.
  • Use infrastructure as code and GitOps to deploy, configure, validate, upgrade, and recover services consistently across environments.
  • Build workflows for service enablement, model releases, handoff, deprecation, and ongoing operations; replace repeatable manual work with reliable automation.
  • Define and instrument SLIs and SLOs for inference and control plane services, including availability and latency, use error budgets to guide reliability improvements, and make production health visible to partner teams.
  • Participate in on-call and incident response, troubleshoot failures across routing, model runtimes, software, and infrastructure, and turn recurring issues into automation and durable fixes.
  • Collaborate with model, platform, storage, networking, security, and GPU infrastructure teams to design and operate services safely at scale.

Qualifications

  • 8+ years of experience building or operating production services and large-scale distributed systems, including hands-on automation.
  • Strong programming skills in Python, Go, or a comparable language, with experience developing tools for production operations.
  • Experience with infrastructure as code, configuration management, or GitOps, and with building automation for repeatable service deployments and changes.
  • Strong knowledge of Linux, Kubernetes, containers, cloud infrastructure, distributed systems, and networking fundamentals; ability to diagnose failures in production.
  • Understanding of Production Engineering principles, including SLIs, SLOs, error budgets, incident response, and reducing operational toil.
  • Experience instrumenting services and using metrics, logs, and traces to understand system behavior and improve reliability.
  • Clear technical communication and ability to work across engineering teams.
  • BS/MS in Computer Science or equivalent practical experience.

Skills

Required:ProgrammingInfrastructure as Code / GitOpsLinux and KubernetesObservability / TelemetryProduction Engineering Principles
Last updated Oct 9, 2026. Interested? Apply on the company site.

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