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NVIDIA

Designs the chips and software that power AI

Director – Software Engineering - Cloud Compute and Infrastructure

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 15 years of overall experience in software engineering, distributed systems, or cloud infrastructure, including at least 7 years leading engineering teams and experience managing engineering managers.
  • Direct engineering ownership of the underlying services of a public or private compute cloud, such as AWS EC2, Google Compute Engine, Azure Compute, OCI Compute, or a comparable infrastructure-as-a-service platform.
  • Strong technical depth in distributed systems, Linux, virtualization, containers, and networking and storage services that support large compute fleets.
  • Experience building software and automation for bare-metal infrastructure, including server provisioning, hardware inventory, firmware or operating-system lifecycle management, and recovery across heterogeneous systems.
  • Experience running production infrastructure with demanding availability requirements, including failure isolation, incident response, observability, and reliable deployment and recovery mechanisms.
  • Ability to guide architecture, evaluate implementation choices, and debug complex interactions among hardware, firmware, drivers, operating systems, and distributed services with senior engineers.
  • A record of sustained ownership as platforms evolve, with measurable improvements in reliability, scalability, or engineering delivery.
  • Strong communication, collaboration, and people-development skills.
  • A degree in computer science, computer engineering, or a related discipline, or equivalent experience.

Responsibilities

  • Lead software engineering teams responsible for cloud compute, bare-metal fleet management, and CI infrastructure, owning architecture, implementation, deployment, and operations.
  • Set the technical direction for compute control planes, resource provisioning, topology-aware placement, reservations, and capacity management across physical servers, virtual machines, and containers.
  • Automate the bare-metal lifecycle, including hardware discovery and inventory, server bring-up, imaging, firmware and driver configuration, out-of-band management, health checks, reprovisioning, and recovery.
  • Build CI services that allocate the right hardware, provision repeatable test environments, record hardware and software configurations, collect diagnostics, and restore systems to a known state; shorten the path from a hardware or software change to actionable validation results.
  • Keep engineering services dependable while supporting evolving preproduction hardware and software; define service-level objectives, isolate failures, improve observability, and turn incidents and recurring test-infrastructure failures into engineering fixes.
  • Measure and improve hardware onboarding time, provisioning speed, CI queue time, productive fleet utilization, recovery time, and cost efficiency as capacity expands.
  • Set engineering standards for design and code reviews, automated testing, secure development, release quality, and safe changes to production systems.
  • Hire, coach, and retain engineers and engineering managers; establish clear ownership, develop technical leaders, and build teams that deliver consistently over multiple release cycles.
  • Partner with hardware, firmware, drivers, networking, storage, security, and validation teams to onboard platforms and diagnose failures across system boundaries; translate engineering users' needs into clear priorities and technical decisions.
  • Work with datacenter operations and facilities teams to bring additional capacity online; connect rack power, cooling, physical topology, and hardware-health telemetry to provisioning, placement, serviceability, and operational readiness.

Desired Qualifications

  • Experience building or operating OpenStack infrastructure, particularly Nova, Neutron, Cinder, or Ironic, or contributing to related open-source projects.
  • Engineering leadership spanning compute control planes and site reliability, including multi-tenant isolation, scheduling, placement, and capacity allocation.
  • Experience with GPU clusters, rack-scale computing, NVLink, InfiniBand or high-speed Ethernet, and AI or high-performance computing workloads.
  • Experience supporting preproduction hardware, new product introduction, or hardware-in-the-loop CI, including repeatable validation environments and systematic regression isolation.
  • Familiarity with liquid-cooled, high-density datacenters and how power, thermal constraints, cooling, and component health affect fleet availability and scheduling.
  • Experience delivering compute platforms across multiple regions, datacenters, or hybrid-cloud environments, including fleet upgrades and workload migration with minimal service disruption.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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