About the Team

The Integrity team builds the systems that protect OpenAI's products, users, and ecosystem from abuse. We work across product engineering, infrastructure, safety, and operations to detect and prevent harmful, fraudulent, deceptive, and adversarial activity at global scale.

As OpenAI builds new ads experiences, we are establishing the integrity foundation that will keep the ads ecosystem safe and trustworthy from the start. This includes protecting advertiser onboarding, detecting unsafe or policy-violating ad content, preventing fraudulent and abusive advertiser behavior, and defending the ads ecosystem against spam, manipulation, and other forms of abuse.

Ads Integrity is a new and highly cross-functional area. The team partners closely with Ads, Product, Safety, Policy, ML, Privacy, Security, and operations teams to build protections directly into the ads platform rather than layering them on after the fact. This is an opportunity to define how integrity works for a new ads ecosystem from first principles.

About the Role

We're looking for an experienced Software Engineer to build the backend systems and infrastructure that keep OpenAI's ads products safe, trustworthy, and resilient to abuse.

In this foundational role, you will design systems that detect, prevent, and respond to harmful, deceptive, fraudulent, or policy-violating activity across the ads lifecycle. The problems span advertiser onboarding and verification, account and behavioral risk, content safety, spam and fraudulent interactions, detection and enforcement infrastructure, and the systems that connect integrity signals and models to real-time product decisions.

This is not an ML-specialist role, but familiarity with ML for Ads integrity is always welcome. You'll work closely with ML engineers and researchers and build systems that consume and operationalize ML-based signals, but your primary focus will be designing and operating robust backend and distributed systems. You'll help determine how signals, rules, models, and human review come together into reliable integrity protections for advertisements that can operate at OpenAI scale.

This role is particularly well suited to an engineer who has built large-scale systems in integrity, trust and safety, anti-abuse, fraud, risk, security, or a related adversarial domain.

You will have significant ownership over what we build and how we build it, partnering across Integrity and Ads to establish the architecture and technical foundations that will protect OpenAI's ads ecosystem as it grows.

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

In this role, you will:

• Design and build large-scale backend systems that detect and prevent harmful, deceptive, fraudulent, or policy-violating activity across the ads ecosystem.
• Build low-latency integrity infrastructure capable of evaluating risk signals and making decisions in or near real time.
• Develop scalable risk-signal pipelines, decision systems, rules and enforcement infrastructure across the advertiser and ads lifecycle.
• Build advertiser onboarding, business verification, account-risk, fraud-detection, and abuse-prevention capabilities that make it harder for malicious actors to enter or exploit the ecosystem.
• Develop systems that support ads-specific content safety and enable the detection and enforcement of unsafe, misleading, deceptive, or policy-violating ads.
• Build protections against spam, fraudulent interactions, manipulation, and other adversarial behaviors that threaten the health of the ads ecosystem.
• Partner with ML teams to integrate classifiers and model-based signals into production integrity systems, including both lightweight real-time protections and more sophisticated asynchronous detection.
• Build feedback loops, review systems, and integrity metrics that improve detection quality while carefully managing false positives and impact on legitimate advertisers and users.
• Create tooling and infrastructure that enable operations and policy teams to investigate abuse and make fast, consistent, and explainable decisions.
• Engineer systems that adapt as adversaries change their tactics and support effective experimentation, monitoring, and incident response.
• Partner closely with Ads Engineering to integrate integrity protections throughout the ads platform without compromising reliability, latency, or product quality.
• Help define the technical strategy and architecture for Ads Integrity as both the product and underlying threat landscape evolve.

You might thrive in this role if you:

• Have significant experience building and operating large-scale backend or distributed systems.
• Have worked on integrity, trust and safety, anti-abuse, fraud, risk, security, business verification, or another domain where systems must operate against sophisticated or evolving adversaries.
• Have built detection, decisioning, enforcement, verification, investigation, or risk infrastructure in production.
• Understand how rules, heuristics, risk signals, ML-based signals, and human review can work together within a dependable production system.
• Are comfortable building ML-adjacent infrastructure and partnering closely with ML teams without needing to be an ML domain expert.
• Have built low-latency, high-throughput services or data pipelines with demanding reliability, correctness, privacy, and security requirements.
• Can reason about false positives, adversarial behavior, explainability, auditability, and the operational impact of automated enforcement.
• Think holistically about threat models, system architecture, data quality, observability, user impact, and ecosystem health.
• Can define technical direction in an ambiguous 0→1 environment and independently drive complex work across teams.
• Communicate clearly and work effectively across engineering, product, policy, safety, security, operations, and machine-learning teams.
• Have experience with ads, ads integrity, advertiser systems, or ads fraud. This is a plus, but not a requirement.
• Are excited to build the integrity foundation for a new product area rather than inherit a mature system.