Why This Job is Featured on The SaaS Jobs
This CPU Storage Tech Lead role stands out in the SaaS ecosystem because it sits at the infrastructure layer that ultimately determines whether software products can be delivered reliably at scale. While the posting is framed around large-scale AI systems and data center buildouts, the work maps to the same foundations that underpin modern SaaS delivery: capacity planning, platform standardisation, and performance per dollar across fleets that must stay available as demand changes.
From a SaaS career perspective, the long-term value is in learning how hardware roadmaps, vendor constraints, and architectural tradeoffs flow through to product-level outcomes like latency, throughput, and service reliability. Owning strategy across CPU, memory, and storage also builds a portfolio of decision-making that translates across cloud platforms and high-usage SaaS environments, especially where infrastructure efficiency and lifecycle management become competitive levers.
This role is best suited to senior engineers who prefer systems-level accountability over narrow component ownership, and who are comfortable influencing across internal stakeholders and external vendors. It will fit professionals motivated by quantitative evaluation, validation in lab and production, and turning ambiguous future workload requirements into concrete platform specifications.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms.
This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments.
Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale.
About the Role
We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure.
In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services.
You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors.
This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions.
Key Responsibilities
Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations.
Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment.
Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines.
Drive server platform decisions involving CPU, memory, NIC, GPU, and storage subsystem integration.
Partner with performance modeling teams to quantify tradeoffs across compute, memory, I/O, and storage bottlenecks.
Work with silicon and hardware vendors on roadmap influence, feature requests, qualification plans, and technical escalations.
Lead bring-up and validation efforts for new CPU and storage platforms in lab and production environments.
Partner with networking and cluster architecture teams to optimize end-to-end node design and data movement.
Support supply chain and sourcing teams with technical vendor assessments and second-source strategies.
Drive reliability, serviceability, and fleet lifecycle planning for compute and storage platforms.
Translate future AI workload requirements into infrastructure platform specifications.
Provide technical leadership across cross-functional stakeholders and executive reviews.
Qualifications
Bachelor’s degree in Computer Engineering, Electrical Engineering, Computer Science, or related technical field; advanced degree preferred.
10+ years of experience in server hardware, systems architecture, data center infrastructure, or hyperscale compute platforms.
Deep expertise in modern CPU architectures (x86, ARM, accelerator host systems) and server platform design.
Strong understanding of memory systems, PCIe/CXL fabrics, NUMA behavior, and platform-level performance constraints.
Experience with storage systems including NVMe, SSD qualification, RAID, distributed storage, object/file systems, or high-performance data pipelines.
Experience evaluating hardware tradeoffs across performance, cost, power, thermals, and supply availability.
Familiarity with GPU clusters and AI training/inference infrastructure strongly preferred.
Experience working directly with OEMs, ODMs, silicon vendors, or storage vendors.
Strong systems thinking with ability to connect component decisions to fleet-level outcomes.
Excellent communication skills with the ability to influence engineering and executive stakeholders.
Proven ability to operate in fast-moving, ambiguous environments with high ownership.
Preferred Skills
Experience designing infrastructure for large-scale AI or HPC environments.
Familiarity with CPU vendor roadmaps across AMD, Intel, and ARM ecosystems.
Experience with distributed storage architectures supporting GPU clusters.
Knowledge of fleet operations, hardware lifecycle management, and production deployments at scale.
Prior experience in hyperscale cloud, AI infrastructure, or advanced compute environments.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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