Engineering Manager, Sensitive Deployments

Responsibilities

• 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

Requirements

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

Nice-to-Haves

• Experience with hyperscaler and government deployments, regulated and high-trust enterprise settings, zero data retention and privacy-constrained deployments
• Background in agentic workloads and harm detection across sequences of actions