Senior Engineer, NCX

NVIDIA; Hamburg; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

NVIDIA seeks a senior NCX Engineer to advance Day 2 operations for NVIDIA Cloud Partners, focusing on production readiness, telemetry, and scalable infrastructure management.

You will work across NVIDIA’s GPU-accelerated platforms, integrating reference architectures into repeatable runbooks, with a strong emphasis on observability and proactive remediation in a large-scale production environment.

Qualifikationen

• BS/MS/PhD in Computer Science, Computer/Electrical Engineering, or related field or equivalent experience.
• 8+ years of experience in infrastructure engineering, SRE, DevOps, cloud platform engineering, or similar roles supporting large-scale production environments.
• Strong experience operating Linux-based distributed systems in production.
• Deep understanding of Kubernetes, containers, cluster scheduling, and large multi-node environments.
• Strong production observability experience: metrics, logging, dashboards, health checks, SLAs.
• Experience crafting automation for infrastructure lifecycle management, failure detection, remediation, upgrades, and config management.
• Strong networking fundamentals and troubleshooting across compute, network, and storage layers.
• Programming or automation in Python, Go, shell scripting, or similar languages.

Aufgaben

• Lead Day 2 operational readiness with NVIDIA Cloud Partners and establish systems, procedures, and automation for scalable management.
• Build continuous infrastructure validation across GPU, CPU, storage, and network health in large AI clusters.
• Establish observability with telemetry, monitoring, dashboards, alerts, and operational signals across compute, GPU, InfiniBand/RoCE, storage, Kubernetes, and AI workloads.
• Develop automated detection and remediation workflows to isolate, repair, and validate unhealthy infrastructure with minimal disruption.
• Refine fleet lifecycle administration for drivers, firmware, Kubernetes nodes, OS patching, configuration management, upgrades, and drift detection.
• Operationalize NVIDIA reference architectures into production runbooks, automation, and measurable standards.
• Define health signals, SLOs, metrics, and acceptance criteria to show reliability and readiness to NVIDIA and partners.
• Build reusable operational frameworks, tooling, runbooks, and reference implementations for multiple NCP environments.

Kenntnisse

Kubernetes experience

Linux proficiency

Observability & monitoring

Automation & SRE tooling

Python/Go scripting

Networking fundamentals

Ausbildung

BS/MS/PhD in CS or related field

Tools

Prometheus

Grafana

OpenTelemetry

Alertmanager

Jobbeschreibung

NVIDIA is hiring an NCX Senior Engineer who is passionate about NVIDIA Cloud Partner (NCP) infrastructure operations to join our DSX team. This role involves working closely with strategic NVIDIA Cloud Partners to build and improve the operational capabilities essential for running large-scale NVIDIA accelerated infrastructure reliably in production.

Your role involves guiding partners beyond the initial cluster deployment and validation phase into advanced Day 2 operations. These operations cover ongoing infrastructure health, observability, lifecycle management, quick remediation, performance validation, and operational readiness. You will engage directly with partner engineering and operations teams to develop consistent approaches that support NVIDIA workloads and the broader external customer environments of the partners. This is a highly technical, hands-on role at the intersection of NVIDIA accelerated computing, cloud infrastructure, distributed systems, and production operations.

What You'll Be Doing

• Lead NCP Day 2 operational readiness efforts. Collaborate directly with NVIDIA Cloud Partners to set up the systems, procedures, automation, and operational methods necessary to consistently manage NVIDIA accelerated infrastructure following initial deployment and activation.
• Build continuous infrastructure validation. Develop and implement methods to continuously validate GPU, CPU, storage, and network health. Do this across large-scale AI clusters to identify degraded infrastructure before it impacts critical training or inference workloads.
• Establish observability and operational telemetry. Help NCPs implement comprehensive telemetry, monitoring, alerting, dashboards, and operational signals across compute, GPU, InfiniBand/RoCE networking, storage, Kubernetes, and AI workloads.
• Develop automated detection and remediation. Build workflows to detect, isolate, drain, repair, validate, and return unhealthy infrastructure to service while minimizing disruption to customer workloads.
• Refine fleet lifecycle administration. Implement scalable strategies for managing sizable GPU fleets, including NVIDIA driver and firmware lifecycle administration, Kubernetes node maintenance, OS patching, configuration management, upgrades, and configuration drift identification.
• Operationalize NVIDIA reference architectures. Translate NVIDIA NCP requirements and reference architectures into production operating practices, validation criteria, runbooks, automation, and measurable operational standards.
• Define operational health and readiness. Develop health signals, SLOs, important metrics, acceptance criteria, and ongoing validation mechanisms that provide NVIDIA and NCPs with clear insight into infrastructure reliability and service readiness.
• Build reusable operational frameworks. Develop tooling, automation, implementation guides, runbooks, operational playbooks, and reference implementations that can be applied consistently across multiple NCP environments.

What We Need To See

• BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
• 8+ years of experience in infrastructure engineering, Site Reliability Engineering, DevOps, cloud platform engineering, systems engineering, or similar roles supporting large-scale production environments.
• Strong experience operating Linux-based distributed systems and cloud infrastructure in production.
• Deep understanding of Kubernetes, containers, cluster scheduling, and the operational lifecycle of large multi-node environments.
• Strong understanding of production observability, including metrics, logging, alerting, dashboards, health checks, and operations guided by service level agreements.
• Experience crafting automation for infrastructure lifecycle management, failure detection, remediation, upgrades, and configuration management.
• Strong networking fundamentals and experience troubleshooting complex distributed systems across compute, network, and storage layers.
• Programming and automation experience using Python, Go, shell scripting, or similar languages.

Ways To Stand Out From The Crowd

• Experience managing extensive GPU or accelerated computing infrastructure that supports AI training and inference workloads.
• Experience with NVIDIA technologies including DGX/HGX systems, CUDA, NVLink/NVSwitch, NVIDIA networking, InfiniBand, RoCE, GPU Operator, Network Operator, or related NVIDIA infrastructure software.
• Proven experience collaborating with NVIDIA Cloud Partners, hyperscale cloud providers, managed AI clouds, or extensive service-provider infrastructure and operating SLOs for large-scale compute infrastructure and using operational data to improve availability, performance, and fleet efficiency.
• Extensive knowledge of infrastructure observability tools including Prometheus, Grafana, OpenTelemetry, Alertmanager, and scalable telemetry pipelines and translating reference architectures or infrastructure requirements into repeatable production operating models across multiple customer or partner environments.
• Knowledge of failure modes related to large distributed AI workloads and the infrastructure features necessary to consistently support extended training and production inference.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated 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. For Poland: The base salary range is 292,500 PLN - 507,000 PLN for Level 4, and 375,000 PLN - 650,000 PLN for Level 5. , , JR2024831