Description
We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems.
You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity.
Key responsibilities include:
- Leading and growing a high-performing Trust & Safety Data Engineering team.
- Defining the roadmap and technical strategy for Trust & Safety data systems.
- Building canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring.
- Creating reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting, evaluation, and production inputs.
- Establishing ownership, documentation, data quality standards, monitoring, and operational rigor for critical datasets and workflows.
We are looking for someone with a strong track record of leading data engineering teams, experience in trust and safety, integrity, abuse prevention, fraud, investigations, risk operations, safety systems, privacy, or adjacent domains, and a deep understanding of data architecture, modeling, pipelines, reliability, privacy, and operational tradeoffs.
Nice to have experience supporting ML systems through feature engineering, training data, labels, model evaluation, or production model pipelines, and experience with launch readiness, monitoring, alerting, incident response, semantic layers, metrics governance, or executive-facing reporting.