# Software Engineer, Shop/Feed Ads
**Company:** [OpenAI](https://scaleengineer.com/companies/openai)
Lead the architecture and development of OpenAI's Shopping/Feed Ads system, managing the complete lifecycle from merchant feed ingestion and catalog indexing to real-time retrieval, ML ranking integration, and high-throughput ads delivery at scale. This role requires deep expertise in distributed systems, product ads infrastructure, and merchant feed ecosystems similar to Google Shopping or Amazon, with independent ownership of complex systems and cross-functional collaboration across ML, product, and design teams.
**Role:** Backend Engineer
**Seniority:** Staff
**Locations:** San Francisco
**Salary:** 347000–445000 USD
[Apply](https://jobs.ashbyhq.com/openai/4d7145cf-ef4e-4a39-b1ef-b58e4e5c06d2)
Canonical: https://scaleengineer.com/jobs/openai/software-engineer-shop-feed-ads
---
## Responsibilities

- Design and Build Feed Ingestion Pipelines: Architect scalable data pipelines that ingest, validate, normalize, and continuously refresh merchant product feeds from retail, travel, and e-commerce sources. Ensure catalog information accuracy, consistency, and availability across all downstream systems serving ads to ChatGPT users globally.
- Develop Scalable Catalog Storage and Indexing Systems: Engineer high-performance storage and indexing architectures supporting large inventories of millions or billions of products. Implement efficient search capabilities, real-time product availability tracking, dynamic pricing updates, and attribute changes with sub-second latency for retrieval operations.
- Build Product Retrieval and Search Infrastructure: Create distributed systems for identifying relevant, eligible products across merchant catalogs in response to user queries. Optimize retrieval efficiency, ranking signals, and filtering logic to support both accuracy and speed at scale.
- Partner with ML Teams on Ranking Integration: Collaborate closely with Ads ML engineering to connect product retrieval systems with ranking models through well-designed interfaces, feature serving infrastructure, and production deployment patterns that maintain reliability and correctness guarantees.
- Engineer Low-Latency Ads Delivery Systems: Build high-throughput, real-time ads serving infrastructure with stringent latency requirements (P99 < 100ms), strong consistency guarantees, and fault tolerance. Ensure deterministic behavior and operational reliability under peak traffic conditions.
- Design Real-Time Event and State Pipelines: Architect distributed event streaming and storage systems supporting catalog freshness monitoring, serving decision logging, and downstream feedback collection. Enable real-time visibility into feed quality, inventory changes, and ads performance metrics.
- Implement Observability and Quality Controls: Build comprehensive monitoring, alerting, and quality assurance systems to detect feed errors, stale inventory, indexing delays, serving failures, and data anomalies. Establish SLOs, canary deployments, and incident response protocols for production stability.
- Define Technical Direction and Drive Complex Projects: Lead architectural decisions from early-stage prototyping through production deployment, managing tradeoffs between freshness, relevance, latency, and operational cost. Drive complex cross-functional initiatives from concept through launch with independent technical ownership.
- Operate Systems with High Engineering Rigor: Maintain production systems through comprehensive testing strategies, continuous monitoring, privacy and security reviews, incident response procedures, and operational best practices. Ensure compliance with data protection standards and platform security requirements.

## Requirements

### education

- {"name":"Bachelor's Degree in Computer Science or Related Field","description":"Formal education in computer science, software engineering, mathematics, physics, or equivalent demonstrating foundational systems thinking and algorithmic complexity analysis."}

### technical

- {"name":"Large-Scale Distributed Systems Design","description":"Proven experience architecting, building, and operating distributed systems handling millions of queries per second with complex state management, consistency requirements, and fault tolerance patterns."}
- {"name":"Product Ads Infrastructure","description":"Direct hands-on experience building core components of product ads systems including retrieval, ranking infrastructure, or delivery at scale. Experience with systems similar to Google Shopping, YouTube product ads, or Amazon product ads."}
- {"name":"Catalog and Merchant Feed Systems","description":"Deep understanding of merchant feed ecosystems, product catalog management, inventory systems, and how feed quality, freshness, and accuracy impact ads relevance and performance metrics."}
- {"name":"Real-Time Data Pipeline Architecture","description":"Experience designing and operating low-latency, high-throughput data pipelines for ingestion, transformation, and serving with demanding correctness and consistency requirements."}
- {"name":"Search and Indexing Systems","description":"Hands-on experience building search infrastructure, full-text indexing engines, filtering systems, and retrieval optimization for ranking or ads serving at scale."}
- {"name":"High-Performance Backend Services","description":"Expertise building low-latency, high-throughput microservices with P99 latency targets under 100ms, strong reliability guarantees, and sophisticated caching and batching strategies."}
- {"name":"ML Systems Integration","description":"Experience designing interfaces between backend systems and machine learning models, including feature serving, model deployment patterns, A/B testing infrastructure, and production ML systems."}

### experience

- {"name":"Staff-Level Backend Engineering Experience","description":"Minimum 12+ years of software engineering experience with at least 5+ years at Staff level or equivalent scope, demonstrating independent technical leadership, architectural design, and large-scale system ownership."}
- {"name":"Product Ads or E-Commerce Platform Experience","description":"Direct experience at Google, Amazon, Meta, Microsoft, or similar companies building or operating product ads platforms, shopping systems, or e-commerce catalog infrastructure at scale."}
- {"name":"0-to-1 Product Development","description":"Demonstrated ability to define technical direction, make architectural decisions under ambiguity, and independently drive complex systems from early prototypes through production deployment at scale."}
- {"name":"Cross-Functional Collaboration","description":"Track record of working effectively with product, design, research, and ML teams to translate business requirements into sound technical architectures with clear tradeoff analysis."}

## Skills

### required

- {"name":"Distributed Systems Architecture","description":"Advanced understanding of distributed system design patterns including consistency models, replication, sharding, consensus protocols, and failure handling in large-scale production environments."}
- {"name":"Backend Systems Design","description":"Expertise in designing scalable backend services, databases, caching layers, and infrastructure supporting millions of requests per second with strict latency and consistency requirements."}
- {"name":"Data Indexing and Search","description":"Deep knowledge of indexing data structures, full-text search engines, ranking algorithms, and query optimization techniques for large-scale information retrieval systems."}
- {"name":"Real-Time Data Processing","description":"Proficiency with real-time event streaming, distributed message queues, stream processing frameworks, and state management for low-latency data pipelines."}
- {"name":"Production Systems Reliability","description":"Expertise in observability, monitoring, logging, tracing, incident response, and operational practices ensuring high availability and correctness in mission-critical systems."}
- {"name":"Performance Optimization","description":"Demonstrated ability to analyze system bottlenecks, optimize algorithms and infrastructure for latency and throughput, and make informed tradeoffs between speed, cost, and resource efficiency."}
- {"name":"Systems Thinking and Tradeoff Analysis","description":"Ability to reason holistically across ingestion, storage, indexing, retrieval, ranking, and serving layers, evaluating architectural decisions against business requirements and operational constraints."}

### preferred

- {"name":"Experience at Massive Scale","description":"Track record operating systems serving billions of users, handling exabytes of data, or managing catalogs of millions of SKUs with real-time freshness requirements."}
- {"name":"Privacy and Security Engineering","description":"Familiarity with privacy-preserving system design, data protection regulations, security reviews, and building systems that handle sensitive user and merchant data responsibly."}
- {"name":"Machine Learning System Integration","description":"Experience deploying ML models in production, designing feature serving systems, implementing A/B testing infrastructure, and collaborating closely with ML researchers and engineers."}
- {"name":"Open Source Systems Expertise","description":"Contributions to or deep expertise with open source distributed systems, databases, search engines, or stream processing platforms commonly used in ads and e-commerce infrastructure."}
- {"name":"Merchant Platform Understanding","description":"Knowledge of advertiser and merchant platform ecosystems, API design for third-party integrations, and systems supporting programmatic advertising."}

## Tech stack

### tools

- {"name":"Container Orchestration","description":"Expertise with Kubernetes, Docker, or container deployment systems for managing distributed services at scale."}
- {"name":"Observability and Monitoring","description":"Proficiency with observability platforms including distributed tracing, metrics collection, log aggregation, and alerting systems for production monitoring."}
- {"name":"CI/CD and DevOps","description":"Experience with continuous integration, continuous deployment pipelines, infrastructure as code, and automated testing frameworks."}
- {"name":"Version Control and Collaboration","description":"Proficiency with Git, code review practices, and collaborative development workflows in large engineering organizations."}

### others

- {"name":"Ads Tech Infrastructure Knowledge","description":"Understanding of ads serving systems, impression tracking, attribution modeling, advertiser account management, and compliance frameworks."}
- {"name":"E-Commerce and Retail Systems","description":"Knowledge of product catalogs, merchant integration patterns, inventory management, pricing systems, and retail data standards."}
- {"name":"API Design and Specification","description":"Expertise designing clean, versioned APIs for internal and external consumption, with strong contracts and backward compatibility considerations."}

### databases

- {"name":"Distributed Databases","description":"Experience operating large-scale databases like Google Spanner, Bigtable, CockroachDB, or similar systems providing consistency and scalability."}
- {"name":"Real-Time Databases and Caches","description":"Expertise with Redis, Memcached, or distributed in-memory systems for high-throughput caching, feature serving, and state management at global scale."}
- {"name":"Search Databases","description":"Hands-on experience with search-optimized databases including Elasticsearch, Apache Lucene, or proprietary inverted index systems."}
- {"name":"Time-Series Data Stores","description":"Familiarity with time-series databases like InfluxDB, Prometheus, or columnar systems for storing and querying metrics, logs, and event data."}

### languages

- {"name":"Python","description":"Likely used for data pipeline orchestration, backend service development, and ML integration within OpenAI's infrastructure."}
- {"name":"C++ or Go","description":"High-performance systems languages for low-latency serving infrastructure and distributed systems requiring maximum throughput and minimal resource overhead."}
- {"name":"SQL","description":"Critical for querying, optimizing, and managing large-scale relational and columnar data stores supporting catalog and transactional workloads."}

### frameworks

- {"name":"Distributed System Frameworks","description":"Experience with frameworks and architectures for building resilient, scalable services including service mesh, orchestration, and communication protocols."}
- {"name":"Search and Indexing Engines","description":"Familiarity with Lucene, Elasticsearch, Vespa, or proprietary indexing systems for building efficient product retrieval and search infrastructure."}
- {"name":"Real-Time Processing Frameworks","description":"Expertise with Apache Kafka, Apache Flink, Spark Streaming, or similar platforms for building real-time data pipelines and event-driven architectures."}

## Benefits

### benefits

- {"name":"Competitive Equity Package","description":"Significant stock options reflecting startup-phase opportunity with meaningful upside potential as OpenAI scales AI products and commercialization."}
- {"name":"Comprehensive Health and Wellness","description":"Medical, dental, and vision coverage with low out-of-pocket costs, mental health support, wellness programs, and preventive care benefits."}
- {"name":"Generous Paid Time Off","description":"Competitive vacation, sick leave, and parental leave policies supporting work-life balance and personal wellbeing."}
- {"name":"Professional Development","description":"Learning budgets, conference attendance, technical training, and mentorship opportunities to develop expertise and stay current with emerging technologies."}
- {"name":"Relocation Assistance","description":"Comprehensive relocation support for new employees relocating to San Francisco or Mountain View Bay Area offices."}
- {"name":"Flexible Work Environment","description":"Collaborative office spaces in San Francisco and Mountain View with flexibility for focused work and distributed collaboration."}
- {"name":"Commuter and Wellness Benefits","description":"Transit subsidies, parking support, on-site fitness facilities, and wellness perks supporting healthy, sustainable commutes and active lifestyles."}

## Compensation

- **max:** 550000
- **min:** 250000
- **currency:** USD
- **stockOptions:** true

## Interview process

### steps

## Full description
## **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.

**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](https://cdn.openai.com/policies/eeo-policy-statement.pdf).

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.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through [this form](https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA). No response will be provided to inquiries unrelated to job posting compliance.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this [link](https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241).

[OpenAI Global Applicant Privacy Policy](https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf)

At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.