Why This Job is Featured on The SaaS Jobs
This role stands out in SaaS because storage is a foundational layer that directly shapes product reliability, cost, and developer experience. The remit spans both research workloads and production systems, which is increasingly common in SaaS-adjacent AI platforms where experimentation and customer-facing availability must coexist. Work across cloud and in-house object stores also reflects a maturity point many SaaS businesses reach when managed services alone stop meeting performance or control requirements.
For a long-term SaaS career, the value lies in owning an infrastructure surface area that other teams build on. Experience with lifecycle management, cross-region movement, and federation patterns translates to any SaaS organization operating at scale, especially those dealing with multi-tenant data, compliance constraints, or global latency targets. Building on Kubernetes and writing production services in a systems language also develops durable skills for platform engineering paths.
The role is best suited to engineers who prefer deep systems work and are comfortable being accountable for operational outcomes, not just feature delivery. It will fit someone who enjoys tracing performance and reliability issues end to end, collaborating closely with internal users, and iterating on interfaces that simplify complex backend choices. It also aligns with professionals who want their infrastructure decisions to influence both near-term experimentation and long-lived product behavior.
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 Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time.
Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution.
About the Role
You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production.
You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust.
In this role, you will:
Build and operate storage services that underpin OpenAI’s research infrastructure
Develop object storage systems across cloud and in-house environments
Build systems for cross-region data movement, replication, and recovery
Design lifecycle management capabilities that keep data durable, available, and cost-effective
Evolve the federation layer that unifies multiple backend systems behind a simple interface
Improve performance, reliability, and operational excellence across the platform
Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads
You might thrive in this role if you:
Have experience building or operating distributed systems in production
Have worked on storage infrastructure, object stores, distributed filesystems, or other data-intensive backend systems
Enjoy owning infrastructure end to end, including debugging and long-term reliability improvements
Write strong production code, ideally in Rust or another systems-oriented language
Are comfortable working with Kubernetes-based systems
Have experience with tools such as Terraform, Grafana, or similar infrastructure and observability tooling
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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