Software Engineer, Core Network Engineering
OpenAI is hiring a Software Engineer, Core Network Engineering in San Francisco, United States. It pays $230k-$342k a year and Level rates it ; you can apply on OpenAI.
Level's read on this job
- Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
- The listed pay starts 37% above the typical software engineer posting on Level.
- Tools and skills the posting cites include Rdma, Roce and Infiniband.
- Level classifies it as a senior role.
- Level lists 793 other open roles at OpenAI.
AI in this role
Core Network Engineer designing and operating high-performance networking infrastructure to support large-scale AI training and inference.
About the Team
The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads.
This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure.
About the Role
We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems.
Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations.
You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance.
This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale.
In this role, you will:
Design, build, and operate networking systems that support large-scale AI training and inference infrastructure
Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems
Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure
Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation
Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-performance GPU interconnects
Define and operationalize networking protocols, readiness criteria, and continuous validation systems
Partner closely with compute, storage, hardware, and infrastructure teams to ensure networking scales predictably with fleet growth
Contribute to architecture decisions around topology design, capacity planning, failure domains, and network reliability
Diagnose complex distributed systems and networking issues across large heterogeneous compute environments
You might thrive in this role if you:
Have experience building or operating large-scale networking or distributed systems infrastructure
Are comfortable working close to the hardware/software boundary
Have experience with Linux networking, kernel systems, NICs, RDMA, or performance-sensitive infrastructure software
Have worked with high-performance networking technologies such as InfiniBand, RoCE, DPDK, or large-scale Ethernet fabrics
Have experience with datacenter networking, WAN systems, or host networking stacks
Enjoy debugging complex systems and performance bottlenecks across multiple layers of the stack
Are comfortable writing production software in languages such as C++, Python, or Go
Have strong systems fundamentals across networking, operating systems, distributed systems, or infrastructure engineering
Are motivated by building infrastructure that directly accelerates frontier AI research and deployment
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.
How we rate this
Software Engineer, Core Network Engineering at OpenAI rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $230k
- Typical software engineer job
- $168k
This posting starts 37% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where networking was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where performance engineering was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Networking, Distributed Systems, Infrastructure, and Performance Engineering. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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