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Staff Engineer, Infrastructure – HPC & AI Compute

Atoms

San Francisco, CAFull-time$224–284K/yrPosted 1 day agoStill listed today

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At a glance

Compensation
$224–284K/yr
Location
San Francisco, CA
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Staff Engineer, Infrastructure – HPC & AI Compute will build physical computing infrastructure for AI, robotics, and autonomous systems. The role spans hardware, software, networking, storage, and data-center infrastructure, from requirements and architecture through deployment and production. The engineer will deliver immediate GPU capacity while establishing a foundation for thousands of GPUs, large-scale CPU compute, and exabyte-scale storage, working closely with infrastructure, AI, and engineering teams.

Skills & qualifications

RequiredNice to have

Skills

Autonomous Vehicles, nice to haveRobotics, nice to haveMachine Learning, nice to haveAutomation, nice to haveStorage, nice to haveML Infrastructure, nice to haveScientific Computing, nice to haveRemote Direct Memory Access, nice to haveArtificial Intelligence, nice to haveTroubleshooting, nice to haveInfrastructure Automation, nice to haveOperating Systems, nice to haveSystems Engineering, nice to haveCloud Infrastructure, nice to haveCapacity Planning, nice to haveData Center, nice to haveDistributed Systems, nice to haveCommissioning, nice to haveBash, nice to haveOEM, nice to haveInfrastructure, nice to haveProcurement, nice to haveSupercomputing, nice to haveGPU, nice to haveKubernetes, nice to haveLinux Server, nice to haveGolang, nice to haveAnsible, nice to haveNetworking Technologies, nice to haveC/C++, nice to haveHigh Performance Computing, nice to haveCeph, nice to haveDistributed Storage, nice to havePython, nice to haveInfrastructure Engineering, requiredData-Center Engineering, requiredPhysical Compute Infrastructure, requiredInfrastructure Initiative Leadership, requiredLinux, requiredServer Hardware, requiredNetworking, requiredGPU/CPU Clusters, requiredDistributed Computing, requiredAI/ML Infrastructure, requiredSimulation, requiredGo, requiredC++, requiredHardware Evaluation, requiredData-Center Infrastructure, requiredIndependent Decision-Making, requiredCross-Functional Collaboration, requiredLarge-Scale AI/ML Training Clusters, nice to haveGPU Supercomputers, nice to haveHigh-Density HPC, nice to haveNVIDIA DGX/HGX, nice to haveInfiniBand, nice to haveRDMA/RoCE, nice to haveSlurm, nice to haveLustre, nice to haveGPFS/Spectrum Scale, nice to haveBeeGFS, nice to havePXE, nice to havexCAT, nice to haveWarewulf, nice to have

Qualifications

8+ Years Infrastructure Experience, requiredBachelor's in Computer Science or Related, requiredEquivalent Practical Experience, required

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off
Parental Leave

Full job description

Who we are

Pronto AI is a global leader in commercializing autonomous vehicle (AV) technology, deploying Autonomous Haulage Systems (AHS) that automate operations in mines, quarries, and construction sites worldwide. While much of the industry remains in R&D, we deliver real, production-ready autonomy that is already operating in the field.

We are on a mission to make mining operations safer, smarter, and more efficient through cutting-edge technology, and we are building toward becoming the world’s first profitable AV technology company.

What you’ll do

As a Staff Engineer focused on HPC & AI Compute Infrastructure, you’ll help build the physical computing infrastructure powering Atoms’ AI, robotics, and autonomous systems. You'll work closely with our Infrastructure, AI, and engineering teams to bring immediate GPU capacity online while architecting the foundation for thousands of GPUs, large-scale CPU compute, and Exabyte-scale storage. This is a hands-on role spanning hardware, software, networking, storage, and data-center infrastructure, where you'll own complex technical challenges from initial requirements through deployment and production.

  • Build AI compute infrastructure from the ground up. Lead the design, deployment, and commissioning of physical GPU and HPC infrastructure, including an intermediate data-center environment in San Francisco, to support autonomous systems, AI/ML workloads, and large-scale simulation.

  • Architect for scale. Define the technical foundation to grow from initial deployments to thousands of GPUs, large-scale CPU compute, and Exabyte-scale storage, balancing performance, reliability, scalability, and cost.

  • Own compute and hardware architecture. Evaluate and specify GPU servers, CPUs, memory, networking components, storage systems, and rack configurations based on workload requirements and infrastructure constraints.

  • Design high-performance networking and storage. Work across cluster interconnects, high-bandwidth networking, distributed storage, and data movement to support compute-intensive workloads.

  • Partner on physical data-center delivery. Collaborate with facilities, real estate, and infrastructure teams to translate compute requirements into power, cooling, rack density, space, and connectivity specifications.

  • Drive infrastructure deployment end to end. Work with hardware manufacturers, vendors, and internal teams on technical evaluations, bills of materials, procurement planning, installation, integration, validation, and production readiness.

  • Automate infrastructure operations. Develop tooling and processes for bare-metal provisioning, configuration management, monitoring, hardware validation, incident response, and failure recovery to make deployments repeatable and reliable.

  • Own capacity planning and operational reliability. Anticipate infrastructure bottlenecks, troubleshoot complex hardware and software issues, and continuously improve performance, utilization, and availability as compute demand grows.

What we’re looking for

We're looking for a hands-on infrastructure engineer who has experience building and scaling physical compute environments, from initial system design through deployment and production. You should be comfortable working across hardware, software, networking, storage, and data-center infrastructure, bringing deep technical expertise and the ability to lead complex engineering initiatives. We're looking for someone who can move quickly to deliver immediate compute capacity while building the technical foundation for long-term scale.

Basic qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent practical experience.

  • 8+ years of experience in infrastructure engineering, systems engineering, high-performance computing, data-center engineering, or related technical disciplines.

  • Demonstrated experience designing, deploying, commissioning, or significantly expanding physical compute infrastructure, including HPC clusters, GPU systems, or large-scale data-center environments.

  • Proven ability to lead complex infrastructure initiatives from technical requirements and architecture through implementation, production readiness, and ongoing operations.

  • Strong systems engineering foundation across Linux, server hardware, networking, and storage, with deep technical expertise in multiple areas.

  • Experience working with high-performance or large-scale computing environments, including GPU/CPU clusters, distributed computing, AI/ML infrastructure, simulation, or comparable workloads.

  • Hands-on experience developing infrastructure automation or tooling using Python, Go, Bash, C++, Ansible, or similar technologies.

  • Experience evaluating hardware configurations, networking and storage technologies, vendor solutions, and performance, reliability, and cost tradeoffs.

  • Working knowledge of data-center infrastructure requirements, including power, cooling, rack density, cabling, and network connectivity.

  • Strong troubleshooting skills and experience diagnosing complex production issues across hardware, operating systems, networking, and storage.

  • Ability to operate independently in fast-moving environments, navigate ambiguity, collaborate across engineering disciplines, and drive technical decisions without relying on established processes.

Nice to have

  • Experience building or operating large-scale AI/ML training clusters, GPU supercomputers, or high-density HPC environments.

  • Experience in industries such as AI infrastructure, autonomous vehicles, robotics, scientific computing, semiconductor engineering, hyperscale data centers, or GPU cloud infrastructure.

  • Familiarity with NVIDIA DGX/HGX systems, InfiniBand, RDMA/RoCE, Slurm, Kubernetes, or other HPC and distributed computing technologies.

  • Experience with distributed storage technologies such as Ceph, Lustre, GPFS/Spectrum Scale, BeeGFS, or similar systems.

  • Experience with bare-metal provisioning and cluster automation using PXE, xCAT, Warewulf, NVIDIA Base Command Manager, or comparable tools.

  • Exposure to modular data centers, liquid cooling, high-density rack deployments, and large-scale power and cooling infrastructure.

  • Experience working directly with hardware OEMs, infrastructure vendors, procurement teams, and facilities partners on capacity planning, infrastructure deployments, and capital expenditure decisions.

Why join us

  • Work on real, production-deployed autonomy.

  • Build technology that directly improves safety, efficiency, and productivity.

  • Tackle complex challenges in demanding, real-world environments.

  • Be part of a fast-moving team with high ownership and impact.

  • See your work deployed and making a difference in the field.

  • Collaborate closely with experienced engineers and industry operators.

What else you need to know

This role is based in our San Francisco office location. As a company driven by innovation and continuous change, close collaboration is essential. We’re constantly reimagining our industry, creating new products, and refining our processes, and we do our best work together. That’s why all of our office-based teams work onsite, five days a week.

The base salary range for this role is $224,000 - $284,000 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also be eligible for equity awards.

Benefits Summary (USA Full-Time Exempt Employees):

  • Medical, Dental, Vision, Disability, and Life Insurance

  • Flexible Spending Account / Health Savings Account Options

  • 401(k)

  • Equity

  • Sick Time, Unlimited Flexible Time Off, and Paid Holidays

  • Paid Parental Leave

  • Pre-Tax Commuter Benefit Plan

  • Team lunch in our SoMa office every Tuesday and Thursday

Benefits are subject to change at the company's discretion. Pronto accepts applications on an ongoing basis.

Ready to join us as we serve those who serve others?

#LI-Onsite

How this job compares

Set against the 5,000 open Infrastructure Engineer jobs on Olive Jobs, counted November 11, 2026.

Pay
  • This posting$224–284K/yr
  • California median$170–252K/yr744 salary ranges
  • US median$121–235K/yr4,248 salary ranges

This range's midpoint, $254K, is 19% above the California median midpoint ($213K) — in the top quarter of Infrastructure Engineer salary ranges in California.

Openings
Olive Jobs lists 922 open Infrastructure Engineer jobs in California and 5,000 across the US. 10% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 8 years of experience; Infrastructure Engineer postings that state a minimum ask for 6 years at the median (3,846 postings).
Education
689 of the 5,000 open Infrastructure Engineer jobs (14%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 11, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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