Why This Job is Featured on The SaaS Jobs
This Software Engineer role stands out in the SaaS ecosystem because it sits at the platform layer where product reliability and research velocity depend on robust data acquisition and cluster operations. The remit spans systems close to hardware alongside Kubernetes-era orchestration, reflecting a company environment evolving from bespoke infrastructure toward more standardised, scalable foundations. That transition is a common inflection point for SaaS and AI-adjacent platforms that need repeatable deployment patterns without losing performance or control.
For a long-term SaaS career, the value is in building judgement across the full infrastructure lifecycle: provisioning, automation, observability, and incident-driven debugging across networking, storage, and compute. Work that reduces manual operations through software is especially transferable, since mature SaaS organisations reward engineers who can turn operational pain into durable tooling and abstractions. The proximity to internal “customers” also mirrors product engineering dynamics, just applied to developer and researcher workflows.
This role best fits engineers who prefer end-to-end ownership and are comfortable moving between code and operations depending on what the system needs. It suits someone who enjoys ambiguity in platform work, can collaborate closely with domain specialists, and wants to deepen systems fundamentals while still shipping improvements that compound over time.
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
This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows. The team sits close to research and works across infrastructure, systems, and automation to make sure researchers have the tools and environments they need to move quickly.
The work spans software engineering, infrastructure, systems administration, cluster operations, and reliability engineering. As OpenAI’s infrastructure evolves from bespoke bare-metal systems toward more standard, scalable platforms, the team needs engineers who can understand how systems work end-to-end and build the right abstractions without reinventing the wheel.
About the Role
As a Software Engineer on this team, you will build and operate the infrastructure that supports frontier research and critical research-facing systems. You will work on systems that sit close to the metal, but the role is not limited to classic operations or sysadmin work. We are looking for someone who can reason about networking, bootstrapping, Kubernetes, scalability, automation, and reliability - while also writing software to make these systems better over time.
This role is a strong fit for an independent, high-ownership engineer who enjoys reliability-heavy infrastructure work but still wants to build. You do not need to come in as a kernel expert or highly algorithmic optimization engineer, but you should be deeply curious about infrastructure, comfortable debugging complex systems, and excited to support researchers doing novel work.
We expect you to:
Build and operate reliable infrastructure for research workloads and research-facing services.
Support and improve systems across data infrastructure, processing, crawl and ingest, caching, search, observability, and clusterwide services.
Improve cluster bootstrapping, provisioning, automation, and deployment workflows.
Debug issues across networking, compute, storage, orchestration, and service reliability layers.
Build software and automation that reduce manual operational work and improve system reliability.
Partner closely with researchers, infrastructure engineers, and service owners to understand system needs and translate them into durable solutions.
Help evolve existing infrastructure toward more scalable, maintainable, and standard patterns.
Take ownership of critical systems and drive work independently from problem definition through execution.
You might thrive in this role if you:
Have strong systems fundamentals and understand how infrastructure scales in practice.
Are comfortable with Linux, networking, Kubernetes, provisioning, and distributed systems operations.
Can write software to automate, debug, and improve infrastructure systems.
Have a strong execution mindset and can independently drive ambiguous infrastructure work.
Enjoy supporting a wide surface area of systems, from research tooling to platform services.
Are pragmatic about when to build custom systems versus using existing, well-supported tools.
Care about building reliable systems that make researchers faster and reduce operational friction.
Nice to have:
Experience with PXE boot, cluster provisioning, bare-metal infrastructure, or large-scale fleet management.
Experience operating Kubernetes or similar orchestration systems at scale.
Experience with infrastructure-as-code, CI/CD, observability, or deployment automation.
Experience supporting search infrastructure, data platforms, ingest systems, or large-scale research workflows.
Experience with Git-based workflows and internal developer tooling.
Prior experience in environments where reliability, scale, and speed all matter.
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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