# Software Engineer, Ads Integrity

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Fullstack Engineering
**Salary:** $293k – $385k/yr
**Experience:** 10+ years
**Skills:** Distributed Systems, Machine Learning, Fraud Detection, risk signals, adversarial systems, low-latency services, Data Pipelines, Observability, auditability, privacy
**Posted:** 2026-07-21

> Build large-scale integrity systems to detect and prevent harmful, deceptive, or fraudulent ads and advertiser behavior at OpenAI. Requires 10+ years building distributed systems in ads integrity, trust & safety, fraud, or security, plus experience combining rules, ML signals, and human review in production.

## Job Description

## 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.

## 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.
- 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.

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