Software Engineer, Ads Integrity

OpenAI•San Francisco, CA

1d•$293,000 - $385,000•Onsite

About The Position

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. We’re looking for an experienced Software Engineer to build the integrity systems that keep OpenAI’s ads products safe, trustworthy, and resilient to abuse. In this foundational role, you will design infrastructure that detects and prevents harmful, deceptive, fraudulent, or policy-violating ads and advertiser behavior at scale. This role is well suited to an engineer who has built large-scale systems in ads integrity, trust and safety, anti-abuse, fraud, security, risk, or a related domain—and who wants to apply that experience in an ambiguous 0→1 environment. You will work across risk signals, detection and enforcement platforms, review tooling, adversarial resilience, advertiser controls, and integrity measurement. We are hiring engineers who can independently own complex systems, make sound technical tradeoffs, and help define what should be built. You will collaborate with Ads Delivery, Ads ML, Product, Research, Safety, Policy, Privacy, Legal, Security, and operations teams to create a high-integrity ads ecosystem from first principles. This role is based in San Francisco. We offer relocation assistance to new employees.

Requirements

10+ years of experience building and operating large-scale distributed systems, ideally in ads integrity, trust and safety, anti-abuse, fraud, security, risk, or an adjacent domain.
Understand adversarial systems and have built detection, decisioning, enforcement, verification, or investigation capabilities.
Have combined rules, heuristics, machine-learning signals, human review, and feedback loops into dependable production systems.
Can reason about precision and recall, false positives, explainability, auditability, appeals, and the operational effects of automated enforcement.
Have built low-latency, high-throughput services or data pipelines with demanding reliability, correctness, privacy, and security requirements.
Are comfortable partnering with policy, operations, legal, safety, security, product, and machine-learning teams on ambiguous and sensitive problems.
Think holistically across threat models, architecture, data quality, observability, user impact, and advertiser trust.
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 safety, fairness, system health, and long-term ecosystem quality.

Responsibilities

Design and build real-time and offline systems that detect harmful, deceptive, fraudulent, or policy-violating ads, advertisers, creatives, and landing experiences.
Develop scalable risk-signal pipelines, rules and model-serving infrastructure, decision systems, and enforcement workflows across the ads lifecycle.
Build advertiser-verification, account-risk, abuse-prevention, and fraud-detection capabilities that raise the cost of adversarial behavior.
Create review and investigation tools that help operations and policy teams make fast, consistent, and explainable decisions.
Design feedback loops, labeling systems, and integrity metrics that improve detection quality while managing false positives and user impact.
Partner with Ads Delivery and Ads ML to integrate integrity checks into retrieval, ranking, auctions, pacing, and serving without compromising reliability or latency.
Engineer resilient systems that adapt to changing adversarial tactics and support safe experimentation and effective incident response.
Define the technical strategy and roadmap for ads integrity across OpenAI’s monetization stack.
Operate systems with high engineering rigor through testing, observability, auditability, privacy and security reviews, and strong operational practices.