About the Team

The Integrity team builds the systems OpenAI uses to understand, prevent, and respond to misuse across our products. We partner with Product, Policy, Safety Systems, User Operations, Security, Legal, Privacy, OpenAI for Government, and research teams to turn policy and threat models into product controls, review workflows, measurement systems, and enforcement paths.

About the Role

We are hiring a Senior Engineering Leader for Integrity's engineering efforts for Sensitive Deployments where model capabilities, customer requirements, deployment environments, privacy considerations, and misuse risks raise the operating bar significantly. These include hyperscaler and government deployments and other high-stakes environments, regulated and high-trust enterprise settings, zero data retention and privacy-constrained deployments. The workloads are increasingly agentic where harm can emerge across a sequence of actions rather than a single prompt.

The Sensitive Deployments Engineering Manager will focus on high-consequence use cases relevant to government deployments and broader deployment-readiness questions for high-risk domains (e.g., healthcare), while building reusable Integrity capabilities for agentic detection and enforcements in these environments.

We're looking for a hands-on engineering leader to guide a team of senior engineers working on OpenAI's most critical deployments. They will lead both the people and technical execution of the team: hiring and developing engineers, setting a high technical bar, and driving ambiguous, high-priority initiatives from early problem definition to durable production outcomes. They will partner closely with Product, Research, Security, Global Affairs, Sales, Solutions, and customer technical teams, while going deep on architecture, infrastructure, and model behavior when needed.

In this role, you will:

• Lead and grow a team of engineers responsible for complex, high-impact deployments of OpenAI technology in sensitive environments.
• Own end-to-end delivery outcomes across prototype, pilot, production launch, and ongoing operation.
• Partner directly with senior customer stakeholders, technical teams, and implementation partners to scope work, sequence delivery, and remove blockers.
• Set and maintain a high bar for architecture, code quality, testing, observability, reliability, security, and operational readiness.
• Translate field learnings into reusable tools, playbooks, reference architectures, product requirements, and roadmap feedback.
• Help the team make crisp tradeoffs between speed, quality, security, safety, and customer-specific needs.
• Serve as a technical escalation point for deployments where ambiguity, urgency, or mission sensitivity is high.
• Coach engineers on technical judgment, customer communication, prioritization, and operating calmly under pressure.
• Build team mechanisms that let the group scale without adding unnecessary process or complexity.

You might thrive in this role if you:

• Bring 10+ years of engineering or technical delivery experience, including 4+ years managing high-performing engineers.
• Have led customer-facing, forward-deployed, platform, infrastructure, security, or applied AI teams through ambiguous production deployments.
• Have experience working with government, defense, intelligence, public sector, critical infrastructure, or similarly sensitive/regulated customers.
• Can credibly engage senior executives, mission owners, security stakeholders, and deeply technical ICs.
• Have strong technical depth across full-stack software, cloud infrastructure, APIs, data systems, security, and production operations.
• Are comfortable reviewing or writing production-grade code in Python, JavaScript/TypeScript, or similar languages.
• Understand deployment models involving Azure, AWS, Kubernetes, Terraform, identity, access controls, encryption, monitoring, and compliance requirements.
• Can turn one-off customer work into reusable systems, platform capabilities, and durable team practices.
• Simplify complex work, make fast and sound decisions under pressure, and communicate tradeoffs clearly.
• Are personally committed to the safe and beneficial deployment of AI.