Why This Job is Featured on The SaaS Jobs
This Software Engineer, Fleet Hardware Health role stands out in the SaaS ecosystem because it sits at the reliability layer that makes always on, usage driven products viable. Rather than focusing on application features, the work targets the compute fleet underpinning model training and production services, where infrastructure behavior directly affects customer facing uptime. The remit touches data center scale operations, GPU heavy environments, and observability, all increasingly central to modern AI enabled SaaS delivery.
For a long term SaaS career, this kind of position builds durable leverage in how services are kept stable as complexity rises. The emphasis on automation for detection and remediation aligns with how mature SaaS organizations reduce toil while improving consistency. Experience partnering across clusters, networking, and infrastructure also maps well to later roles in platform engineering, SRE, or reliability focused product infrastructure, where cross system reasoning is a differentiator.
The role is best suited to engineers who prefer deep investigation over surface level fixes and who enjoy turning ambiguous operational signals into repeatable systems. It fits someone comfortable balancing building and operationalizing, and interested in the mechanics behind scalable service delivery, even without prior hardware specialization.
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 Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth.
About the role
As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise.
Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure.
Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale.
In this role, you will:
Build and maintain automation systems for provisioning and managing server fleets.
Develop tools to monitor server health, performance, and lifecycle events.
Collaborate with clusters, networking, and infrastructure teams.
Partner with external operators to ensure a high level of quality.
Identify and fix performance bottlenecks and inefficiencies.
Continuously improve automation to reduce manual work.
You might thrive in this role if you have:
Experience managing large-scale server environments.
A balance of strengths in building and operationalizing.
Proficiency in Python, Go, or similar languages.
Strong Linux, networking, and server hardware knowledge.
Comfort digging into noisy data with SQL, PromQL, and Pandas or any other tool.
Prior hardware expertise is not required for this role.
Bonus Skills:
Experience with low level details of hardware components, protocols, and associated Linux tooling (e.g., PCIe, Infiniband, networking, power management, kernel perf tuning)
Knowledge of hardware management protocols (e.g., IPMI, Redfish).
High-performance computing (HPC) or distributed systems experience.
Prior experience developing, managing, or designing hardware.
Familiarity with monitoring tools (e.g., Prometheus, Grafana).
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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