Meta is seeking a Program Manager, Safety & Preparedness for the Meta Superintelligence Labs organization. This role is crucial for driving the development, coordination, and execution of safety and preparedness programs that support the responsible scaling of MSL's AI capabilities. Key responsibilities include building and managing safety frameworks, coordinating cross-functional preparedness initiatives, overseeing risk assessment programs, and ensuring organizational readiness for emerging AI safety challenges. The candidate will demonstrate exceptional program management proficiency, proven experience in safety operations or preparedness planning within complex technical organizations, excellent written communication skills, and the ability to seamlessly transition between providing strategic counsel and managing detailed program execution. This individual must be a collaborative team member, prepared to thrive in a dynamic, high-expectation professional environment. Entrepreneurial acumen, proven ability to manage complex and sensitive information with agility, and a commitment to exercising the highest level of discretion are desired. This role is designed for a highly strategic, execution-oriented program manager who can support a fast-moving AI organization with focus, accountability, and scale in the critical domain of AI safety and preparedness.
Responsibilities
Design, implement, and manage cross-functional safety and preparedness programs Build working relationships and facilitate collaboration with internal cross-functional teams, including Legal, Policy, Trust & Safety, Finance, HR, and Engineering, to enable seamless execution of safety programs, remove friction, and advance organizational safety objectives Maintain a real-time understanding of MSL's highest-priority safety and preparedness initiatives by participating in key forums, tracking progress against critical goals, and ensuring leadership is consistently equipped with clear insights, recommendations, and decision context Draft and curate executive-level documents, safety assessments, program status reports, presentations, and briefing materials for internal and external engagements, and drive disciplined follow-through to ensure alignment and accountability Coordinate data collection related tasks across safety areas (e.g., agents safety, red teaming, deception, containment, CBRN, cyber defense, etc.) Manage access and permissions related to sensitive data (e.g., CBRN ITAR compliance, testing environments for loss of control, etc.) Support compute planning and analysis, including team compute usage optimization and resource allocation Drive AAISF-related commitments and dangerous capability enforcement programs (e.g., KYC program for cybersecurity and CBRN)
Qualifications
8+ years of proven experience in program management, safety operations, preparedness planning, or a similar role within a fast-paced and complex technical organization Demonstrated ability to manage multiple programs and priorities, including developing safety frameworks, tracking risk mitigation efforts, and coordinating cross-functional readiness activities Experience working with senior leadership, including navigating company policies and procedures related to safety and compliance Excellent written and verbal communication skills, with the ability to draft executive briefs, safety assessments, and presentations Proven track record of organizing, developing, and executing strategic programs that deliver measurable results Proficient understanding of Artificial Intelligence and associated safety considerations Bachelor's degree or foreign equivalent Master’s of Business Administration (MBA) degree or foreign equivalent Experience in AI safety, trust & safety, or technical risk management programs Background in incident response, business continuity, or organizational preparedness planning Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies