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Copilot Security is at the heart of Microsoft’s mission to deliver trusted, human-centered AI experiences. We make trust, safety, and resilience foundational to every Copilot interaction, across devices, platforms, and ecosystems. Our work spans secure identity flows, defenses against emerging threats like prompt injection, and privacy-first systems that scale globally. As a Principal Technical Program Manager for Copilot Security, you will drive the development and orchestration of advanced security features and programs that protect Copilot and its users from emerging threats, including prompt injection, adversarial manipulation, and intent-based attacks. Your work will span the design and deployment of security control sets, real-time detection systems, and defense-in-depth strategies for AI-powered products at global scale. You’ll collaborate with engineering, research, and product teams to transform complex security challenges into paved roads for innovation, ensuring every Copilot interaction meets the highest standards of privacy, compliance, and reliability. This is a rare opportunity to shape the security architecture for AI experiences used by hundreds of millions worldwide, influencing both technical direction and organizational culture. If you thrive on solving hard problems, driving clarity in ambiguity, and building systems that scale with trust, we want you on this team.
Job Responsibility:
Lead and orchestrate AI security programs across multiple client surfaces (desktop, web, mobile), aligning roadmaps and milestones with partner teams and Microsoft’s central security ecosystem
Drive feature development for prompt injection defenses, intent-based detection systems, and security control sets, leveraging the latest research and industry frameworks (e.g., NIST COSAIS, CSA AI Controls Matrix)
Partner with engineering, research, and product managers to scope initiatives, define success metrics, and plan phased delivery that reduces risk and accelerates customer value
Implement novel defense-in-depth strategies like cross-prompt isolation (XPIA), adaptive threat detections, agentic adversarial testing, and secure model lifecycle practices
Ensure data quality, privacy, and compliance for AI-related telemetry and signals
work with stakeholders to meet all regulatory and security requirements for shipping features at scale
Drive execution excellence: define schedules, milestones, KPIs, and review cadences
track progress, manage dependencies, surface risks, and ensure on-time delivery
Communicate program status, insights, and blockers with leadership and stakeholders
clarify ownership, hold teams accountable, and cultivate durable cross-org partnerships
Manage program execution and stakeholder engagement across geographically distributed teams, proactively addressing time zone challenges and fostering effective communication
Schedule and facilitate meetings, reviews, and decision-making sessions that accommodate global team members, ensuring all voices are heard and progress remains on track
Requirements:
Bachelor's Degree AND 6+ years experience in engineering, product/technical program management, data analysis, or product development OR equivalent experience
3+ years of experience managing cross-functional and/or cross-team projects
Nice to have:
3+ years of hands-on experience with AI security, including prompt injection defenses, adversarial ML, and secure software development practices
Proven track record driving feature launches and large-scale rollouts in complex systems, ideally across multiple client surfaces (desktop, web, mobile)
Experience defining long-term program vision and strategy for security/AI projects
proficiency with OKRs and KPI-driven execution
Excellent communication, collaboration, and influence skills
ability to crisply communicate technical concepts to diverse audiences
Ability to thrive in fast-paced, ambiguous environments while driving clarity, alignment, and results
Demonstrated experience collaborating with globally distributed teams
Ability to adapt communication and project management approaches to suit diverse cultural and working styles
Familiarity with security control frameworks for AI (e.g., NIST COSAIS, CSA AI Controls Matrix, SANS Critical AI Security Guidelines)
Experience working with Microsoft’s security ecosystem or similar large-scale AI platforms
Practical knowledge of risk-based authentication, secure API design, and data loss prevention (DLP) technologies
Understanding of privacy-by-design principles and compliance requirements (e.g., GDPR, regional data regulations) for AI data
Experience with incident response, red teaming, and threat modeling for AI/ML systems