Technical Program Manager, Storage & Data Infrastructure

About the Team

OpenAIs data and storage infrastructure spans data platforms online databases and file/object storage. These systems underpin data ingestion and processing durable persistence indexing and retrieval and product file experiences. As frontier models and agents evolve how they use memory history and snapshots the underlying architecture increasingly shapes the capabilities products can deliverand their latency reliability cost and efficiency.

About the Role

We are looking for a technically deep TPM to independently define and lead multiple programs across data platforms online databases and storage infrastructure. You will connect model product and data-consumer requirements to architecture and work with the relevant engineering teams to take new capabilities through production adoption and repeatable expansion.

The design scope is exabyte-scale storage and infrastructure spanning multiple millions of CPU cores. The challenge is not simply forecasting more resources: it is making complete workload-ready capacity repeatable with a clear path from product requirements through architecture deployment and validation. A data pipeline database query file operation or execution snapshot can affect whether a product or agent succeeds; you will connect those outcomes to the systems underneath.

This role is based in San Francisco CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role you will:

• Translate model product and data-platform needs into precise access patterns consistency durability freshness availability and scalability requirements. Connect memory history retrieval and resumable work to capability and end-to-end latency.

• Partner with engineering to transform data and storage architecture into repeatable scale units: standardized provisioning placement routing data movement and readiness checks that bring storage compute and networking online together. Tie each expansion to the workloads it can serve.

• Lead cross-stack programs connecting ingestion and processing databases and indexes and file/object storage. Make data ownership schema compatibility change-data-capture replay and consumer-readiness contracts explicit so the full data path remains correct and usable.

• Make cost and efficiency architectural inputs. Evaluate physical versus logical footprint index and replication amplification redundant copies tiering caching and network movement against the cost of serving useful workloads.

• Drive resilience and recovery programs with explicit failure scenarios and validation. Distinguish database backup failover and point-in-time recovery from execution/workspace save-and-restore; verify correctness recovery time safe resumption and isolation from live traffic.

• Coordinate lifecycle correctness across files objects databases and data platforms including metadata retention deletion and snapshots. Incorporate privacy access control auditability and residency requirements into the design and consumer contracts.

• Lead adoption and major migrations through compatibility checks representative workload testing staged cutovers rollback and operational handoff. Improve APIs guardrails and self-service so new capacity and capabilities can be consumed predictably.

• Measure architecture changes through product and platform outcomes: task completion and continuity data freshness query/retrieval and snapshot latency throughput reliability and cost/efficiency. Use those results to drive durable performance and operational improvements.

You might thrive in this role if you:

• Have independently owned complex production programs in data platforms databases or storage infrastructure and can explain the architectural decisions your contribution and the resulting impact.

• Have deep working knowledge of hyperscaler/cloud storage technologies such as Amazon S3 or Azure Blob Storage including their performance placement resiliency and cost constraints.

• Understand the full data and storage stack: product access patterns and APIs; ingestion and processing; databases storage engines and indexes; caching replication and data movement; and the durable-storage CPU and network layers that support them.

• Can translate model product and data-consumer needs into precise platform requirements challenge assumptions and define evidence that a capability recovery path or scaling change is ready.

• Have led delivery across product model data database storage and infrastructure teams especially where no single team owns the end-to-end result.

• Can use workload evidence to make tradeoffs across capability correctness reliability latency and cost/efficiency and build mechanisms that improve decisions as requirements change.

• Communicate complex decisions clearly and maintain ownership through production adoption not only a launch milestone.

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 OpenAIs 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 addition job duties require access to secure and protected information technology systems and related data security obligations.

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Required Experience:

IC