Strategic Sourcing Manager, Data Center Infrastructure, Electrical & Mechanical
OpenAI · San Francisco, CA · Cloud, IT and infrastructure · posted today
OpenAI · San Francisco, CA · posted 87 days ago
By AtiveSite · Published 07/11/2026 · Updated 09/11/2026 · Every figure is linked to its source below.
| Employer | OpenAI |
|---|---|
| Location | San Francisco, California |
| Field | Technology › Software engineering |
| Level | not stated |
| Source category | Scaling, Compute |
| Posted | 2026-08-14 (87 days ago) |
| Work arrangement | A remote or flexible location is listed |
| Pay | Not published in the source listing |
About the Team:
Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams.
Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage.
About the Role
We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you.
Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, topology, firmware, thermals, and failure modes, or design abstractions that make heterogeneous clusters feel like one coherent platform.
We do not expect every candidate to have worked at every layer. Some engineers will go deep on systems performance, kernel or runtime behavior, large-scale networking protocols, RDMA, NCCL, GPU hardware behavior, benchmarking, scheduling, or hardware reliability; others will make the platform more usable through APIs, tools, workflows, and developer experience. The common thread is strong engineering judgment and excitement about making enormous compute systems faster, more reliable, and easier to use.
This is a general opening for Compute Infrastructure. We will consider candidates for teams across Compute Infrastructure and match you based on your strengths, the problems that motivate you, and where the infrastructure needs are highest.
Where you might work
Compute Foundations: Build the low-level platform primitives that make heterogeneous hardware, providers, and data centers repeatable, automatable, and operable at scale.
Fleet / Orchestration: Turn raw capacity into reliable, efficient clusters and scheduling systems that researchers and product teams can use with minimal friction and great experience.
Core Network Engineering: Build and operate the high-performance networking fabrics, protocols, and observability needed for the largest training and serving workloads.
Hardware Health and Observability: Detect, diagnose, remediate, and prevent hardware and fleet-health issues so usable compute stays high across providers and accelerator generations.
Storage: Build scalable, performant, durable storage abstractions that keep data movement and storage access from becoming a bottleneck to research or products.
Agent Infrastructure: Build sandboxed execution infrastructure for agentic workloads across research and production, with strong isolation, reliability, and scale.
In this role, you will:
Build and deeply optimize reliable system software for large-scale compute systems that run some of the world's most demanding AI workloads
Design and operate infrastructure across accelerators, CPUs, NICs, switches, networking protocols, storage, data centers, cluster orchestration, scheduling, and fleet health
Profile, benchmark, and optimize training workloads across compute, memory, storage, networking, NCCL and collective communication, and cluster scheduling bottlenecks
Create hardware-aware automation that makes provisioning, firmware and driver upgrades, incident response, and day-to-day operations faster and less error-prone
Build CaaS, agent infrastructure, profiling, observability, benchmarking, and platform tools that help researchers, product engineers, and operators launch, debug, and optimize workloads with less friction
Turn operational lessons into better systems, stronger abstractions, and clearer ownership boundaries across teams
Collaborate across research, engineering, security, networking, hardware, and data center teams to make compute capacity more capable and easier to use
You might thrive in this role if you:
Have built or operated distributed systems, infrastructure platforms, high-performance computing environments, large-scale networking systems, Kubernetes clusters, developer tools, or production systems with demanding reliability requirements
Enjoy working across layers of the stack and are comfortable moving between software, hardware, networking, systems performance, reliability, and user needs
Care about making complex infrastructure understandable, observable, and usable for the people depending on it
Can diagnose hard problems under real operational pressure while still investing in long-term engineering quality
Like building leverage for others, whether through APIs, automation, debugging tools, CaaS and agent infrastructure primitives, workflow improvements, or better platform abstractions
Are motivated by scale, efficiency, reliability, and disciplined measurement through benchmarks, profiles, and production evidence
Communicate clearly, take ownership, and work well with teams whose constraints and goals differ from your own
Qualifications
Strong software engineering skills and experience building, operating, or improving production infrastructure systems
Experience in one or more relevant areas such as distributed systems, operating systems, networking protocols, RDMA, NCCL or collective communication, storage, Kubernetes, scheduling, observability, reliability engineering, high-performance computing, GPU infrastructure, CaaS, agent infrastructure, hardware-aware performance optimization, benchmarking, developer experience, or infrastructure tooling
Ability to debug complex system behavior across software, hardware, networking, and workload layers, then turn findings into robust improvements
Comfort with ambiguity, strong ownership, and a bias toward practical, durable solutions
Interest in working on infrastructure that directly enables frontier AI research and product impact
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.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Field: Technology Sub-niche: Software engineering All jobs at OpenAI Jobs in California Jobs in San Francisco, CA San Francisco city guide California state guide San Francisco County economy
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This is a — role in the Technology field (Software engineering) at OpenAI.
We could not match this job title to one occupation in the official wage statistics, so no pay estimate is shown. Pay is not in the source listing; ask the employer for the range and compare in the 240 job niches.
Estimate for a wage earner: 2026 federal brackets and standard deduction (IRS), Social Security 6.2% up to $184,500, Medicare 1.45% (+0.9% above $200,000 single / $250,000 married), and a state rate you set; set your own state tax rate. It ignores credits, pre-tax deductions, local taxes and benefits. Sources: IRS: tax year 2026 inflation adjustments · SSA wage base per Federal Register notice 2025-19763.
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The job is in San Francisco, CA. Below is what the official statistics say about living and working there.
How San Francisco compares. Among the 145 largest places in California, San Francisco is #4 by population, #139 for homeownership (#1 = highest), #20 for remote work (#1 = most), #25 for college degrees (#1 = most). Its county, San Francisco County, is #3 of 58 counties for average pay ($174,103).
San Francisco has 830,235 residents (ACS 2020–2024), about 2.1% of the population of California. It covers 47 square miles of land, which works out to roughly 17,784 people per square mile. The median age is 40.0, 6% older than the state median (40.0 against 37.9).
The median gross rent is $2,476 a month (rent plus utilities), 22% above the state median ($2,476 against $2,036). Over a year that is 21.1% of the median household income. US housing guidance treats housing as affordable when it takes 30% of income or less, so the typical household is under that line. The median home value is $1,394,500, which is 9.9 times the median household income ($140,970); a ratio above 5 usually means buying is out of reach without savings or a second income. 38.2% of households own their home, 32% below the state average (38.2% against 55.9%). A low ownership share points to a rental-heavy market with more apartments and shorter stays.
The San Francisco-Oakland-Fremont, CA metropolitan area has 2,373,920 jobs in the BLS wage survey, and the median pay across all occupations is $74,260 a year, 46% above the national median ($74,260 against $50,980). The biggest occupation groups are office and administrative support (226,320 jobs, median $62,120); management (223,100 jobs, median $176,340); business and financial operations (207,030 jobs, median $112,960). The area is most specialised in computer and mathematical (1.9 times) and life, physical, and social science (1.8 times), where the share of workers is well above the national share. The best-paying groups with at least 5,000 jobs are management ($176,340) and computer and mathematical ($167,770). In 2026M09 the unemployment rate of San Francisco County was 4.0%. 69.6% of residents aged 16 and over are in the labour force. The city lies in San Francisco County; its jobs, pay by industry and GDP are on the county page.
Among workers, 28.6% drive alone, 18.7% use public transit, 9.3% walk, 31.0% work from home. 21.6% of workers commute 45 minutes or more, 11% above the state average (21.6% against 19.4%). Remote work is more common than in the state as a whole, which widens the set of employers a resident can work for without moving.
60.3% of adults aged 25 and over hold a bachelor's degree or higher, 63% above the state share (60.3% against 37.1%). 34.0% of residents were born outside the United States, 26% above the state share (34.0% against 27.0%). The poverty rate is 11.2%, 7% below the state rate (11.2% against 12.0%).
The warmest month is Sep, averaging 59°F (14.9°C), and the coolest is Apr at 53°F (11.6°C). About 515 mm (20 inches) of precipitation falls in a year; Dec is the wettest month (112 mm) and Jul the driest (2 mm). These values come from NASA satellite-based climatology on a grid of about 50 km, so they describe the wider area, not a weather station in the city.
Closest cities in this guide: Daly City (31 miles, rent 3% higher); Pacifica (31 miles, rent 25% higher); San Bruno (34 miles, rent 12% higher); Millbrae (36 miles, rent 32% higher). Rent differences are against San Francisco; use the Compare tab to put any two cities side by side.
Full guide to San Francisco →California guideAll jobs in San Francisco
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Places within 50 miles (straight line) of San Francisco, CA that have a guide, with what living there costs. No pay estimate is shown because the title did not match one occupation.
| Place ⇅ | Distance from the job city ⇅ | Median rent ⇅ | Median home value ⇅ | Median household income ⇅ | Commute 45+ min ⇅ | Rent as % of occupation pay ⇅ | Open jobs there ⇅ |
|---|---|---|---|---|---|---|---|
| San Francisco, CA | 0 mi | $2,476 | $1,394,500 | $140,970 | 21.6% | n/a | Jobs |
| Daly City, CA | 31 mi | $2,551 | $1,115,000 | $123,547 | 19.6% | n/a | Jobs |
| Pacifica, CA | 31 mi | $3,098 | $1,249,800 | $160,523 | 15.5% | n/a | — |
| San Bruno, CA | 34 mi | $2,773 | $1,207,500 | $141,272 | 12.2% | n/a | — |
| Millbrae, CA | 36 mi | $3,272 | $1,934,900 | $163,476 | 21.8% | n/a | Jobs |
| Brisbane, CA | 36 mi | $2,574 | $1,232,200 | $156,169 | 29.8% | n/a | — |
| South San Francisco, CA | 36 mi | $2,802 | $1,188,800 | $136,578 | 15.2% | n/a | Jobs |
| Half Moon Bay, CA | 37 mi | $2,433 | $1,549,500 | $157,884 | 26.7% | n/a | — |
| Burlingame, CA | 38 mi | $2,785 | $2,000,001 | $174,000 | 23.1% | n/a | Jobs |
| Richmond, CA | 40 mi | $1,960 | $668,200 | $95,391 | 28.8% | n/a | — |
| San Mateo, CA | 41 mi | $3,077 | $1,618,700 | $153,504 | 15.8% | n/a | Jobs |
| Berkeley, CA | 41 mi | $2,133 | $1,413,900 | $108,092 | 20.8% | n/a | Jobs |
| Alameda, CA | 42 mi | $2,474 | $1,235,700 | $137,697 | 27.3% | n/a | Jobs |
| Belmont, CA | 43 mi | $2,875 | $2,000,001 | $205,297 | 18.6% | n/a | Jobs |
| Oakland, CA | 44 mi | $1,979 | $929,900 | $101,600 | 21.9% | n/a | Jobs |
| Foster City, CA | 44 mi | $3,501 | $1,838,200 | $199,143 | 20.6% | n/a | Jobs |
| San Carlos, CA | 45 mi | $2,854 | $2,000,001 | $237,470 | 14.9% | n/a | Jobs |
| Redwood City, CA | 47 mi | $2,968 | $1,801,700 | $157,814 | 10.2% | n/a | Jobs |
| San Leandro, CA | 48 mi | $2,186 | $844,200 | $101,420 | 23.7% | n/a | — |
| Atherton, CA | 49 mi | $3,501 | $2,000,001 | $250,001 | 7.0% | n/a | — |
We could not match this title to one occupation, so here are the other sub-niches in Technology, where your skills may carry over:
Cybersecurity (713) Data, analytics and AI (3366) Cloud, IT and infrastructure (1040) Product management (836)
How far San Francisco, CA is from the 20 largest US cities, in straight-line miles (not driving distance). Click a column to sort.
| From ⇅ | Straight-line distance (miles) ⇅ | Population of that city ⇅ |
|---|---|---|
| San Francisco, CA | 0 mi | 830,235 |
| San Jose, CA | 73 mi | 990,138 |
| Los Angeles, CA | 364 mi | 3,857,263 |
| San Diego, CA | 475 mi | 1,389,526 |
| Phoenix, AZ | 678 mi | 1,642,323 |
| Seattle, WA | 684 mi | 754,195 |
| Denver, CO | 986 mi | 718,877 |
| Oklahoma City, OK | 1,420 mi | 697,125 |
| Fort Worth, TX | 1,484 mi | 963,194 |
| Dallas, TX | 1,515 mi | 1,307,930 |
| San Antonio, TX | 1,516 mi | 1,479,835 |
| Austin, TX | 1,530 mi | 979,539 |
| Houston, TX | 1,673 mi | 2,328,253 |
| Chicago, IL | 1,885 mi | 2,711,226 |
| Indianapolis, IN | 1,979 mi | 885,860 |
| Columbus, OH | 2,142 mi | 914,802 |
| Charlotte, NC | 2,332 mi | 903,844 |
| Jacksonville, FL | 2,403 mi | 977,670 |
| Philadelphia, PA | 2,550 mi | 1,579,706 |
| New York, NY | 2,602 mi | 8,483,844 |
| City ⇅ | Straight-line distance ⇅ | Open jobs ⇅ |
|---|---|---|
| Alameda, CA | 42 mi | 38 |
| Belmont, CA | 43 mi | 2 |
| Redwood City, CA | 47 mi | 45 |
| Palo Alto, CA | 54 mi | 298 |
| Sunnyvale, CA | 60 mi | 83 |
| Fremont, CA | 62 mi | 6 |
| Pleasanton, CA | 63 mi | 6 |
| Milpitas, CA | 66 mi | 2 |
| Campbell, CA | 67 mi | 7 |
| San Jose, CA | 73 mi | 698 |
| Capitola, CA | 79 mi | 1 |
| Sacramento, CA | 103 mi | 53 |
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A private-sector role in technology (software engineering) listed 87 days ago. The full description is on this page and on the employer's page.
San Francisco, CA. A remote or flexible location is listed; confirm with the employer which states are accepted.
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The listing does not publish pay, and we could not match the title to one official occupation.
Median rent in San Francisco is $2,476 a month and median household income $140,970 (ACS 2020–2024).
It was posted on 2026-08-14 (87 days ago). Jobs older than 90 days are not shown.
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