Software Engineer, Shop/Feed Ads

About the team

The Monetization team is a new cross-functional group spanning engineering, product, research, and design. We are building the foundational systems that will help OpenAI scale access to intelligence responsibly.

Our mission is to create user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen trust, expand economic opportunity, and support OpenAI’s long-term innovation. We believe monetization should deliver clear user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem for developers and businesses.

The team operates in a greenfield environment, moving quickly through prototyping, experimentation, and iterative deployment. We partner closely across Product, Design, and Research to bring new capabilities into real-world systems at global scale.

About the role

We’re looking for an experienced Software Engineer to lead the design and development of the systems that turn advertiser feeds (eg. retail feeds, travel feeds etc.) into relevant, reliably delivered ads. In this foundational role, you will build across the full ads lifecycle—from ingesting and organizing retailer or travel catalogs into efficient retrieval systems, supporting ranking models, and serving ads at scale.

This role is well suited to an engineer with direct experience in product ads retrieval, ranking, and delivery, along with a strong understanding of merchant feeds and shopping systems such as Google Shopping, YouTube product ads, or Amazon. We also welcome engineers with Senior Staff-level or greater scope who have deep ownership of large-scale catalogs, search and indexing, ads serving, or closely related distributed systems.

You will independently own complex systems, make sound technical tradeoffs, and help define the architecture and roadmap for Shopping/Travel/Feed Ads. You will collaborate closely with Ads ML, Ads Delivery, Product, Design, and Research to connect accurate, fresh advertiser feed information with useful ads experiences in ChatGPT.

This role is based in San Francisco and Mountain View. We offer relocation assistance to new employees.

In this role, you will

• Design and build pipelines that ingest, validate, normalize, and refresh merchant product feeds, keeping catalog information accurate and available for serving.
• Develop scalable catalog storage and indexing systems that make large inventories searchable and reflect changes in product availability, pricing, and attributes.
• Build search and retrieval systems that efficiently identify relevant, eligible products across merchant catalogs.
• Partner with Ads ML to connect product retrieval with ranking models through dependable interfaces, features, and serving infrastructure.
• Engineer low-latency, high-throughput ads delivery systems with strong reliability and correctness guarantees.
• Design real-time event pipelines and distributed storage that support catalog freshness, serving decisions, and downstream feedback.
• Build observability and quality controls to detect feed errors, stale inventory, indexing delays, and serving issues.
• Define technical direction and drive complex projects from early prototypes through production deployment and operation.
• Operate systems with high engineering rigor through testing, monitoring, privacy and security reviews, and strong operational practices.

You might thrive in this role if you

• Have extensive experience building and operating large-scale distributed systems, with direct ownership of product ads retrieval, ranking infrastructure, or delivery.
• Understand merchant feeds and shopping systems, including how catalog quality, product availability, and freshness affect relevance and ads performance.
• Have built systems for shopping or product ads at platforms such as Google Shopping, YouTube, Amazon, or a comparable environment.
• Alternatively, have operated at Senior Staff-level scope or above, leading the architecture and delivery of large-scale catalogs, search and indexing platforms, ads serving, or related backend systems.
• Have built low-latency, high-throughput services and data pipelines with demanding reliability and correctness requirements.
• Can reason across ingestion, storage, indexing, retrieval, ranking, and serving, and make thoughtful tradeoffs between freshness, relevance, latency, and cost.
• Are comfortable partnering with machine-learning teams to bring ranking models and signals into dependable production systems.
• Can define technical direction in an ambiguous 0→1 environment and independently drive complex work across teams.
• Communicate clearly and make technical decisions grounded in user value, merchant experience, and long-term system health.