Technical Manager, Data Engineering, Trust & Safety
OpenAI is seeking a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This hands-on leadership role involves setting strategy, shaping data architecture, coaching engineers, and driving execution on high-impact data systems to build privacy-safe data foundations for understanding, detecting, investigating, and mitigating abuse and safety risks across OpenAI products.
The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely.
The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting.
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.
This role is based in our San Francisco HQ. We offer relocation assistance to new employees.
Please note: this role may involve work related to sensitive or concerning safety, abuse, fraud, or user-risk domains. Strong discretion, judgment, and resilience are essential.
Posted June 11, 2026