Technical Program Manager (TPM) at the staff level to lead and deliver large-scale, cross-organizational technical programs. In this role, you will apply deep technical expertise and strategic program leadership to drive alignment across multiple engineering and product teams, translate complex technical challenges into structured execution plans, and influence the technical direction of programs that have broad organizational impact. You will partner with engineering leaders and cross-functional stakeholders to define program strategy, manage risk, and deliver outcomes that advance Meta's technical infrastructure and product goals at scale.

Responsibilities

Define and drive the end-to-end strategy and execution of large-scale, cross-organizational technical programs spanning multiple engineering pillars, from technical assessment and system design through implementation and post-launch evaluation
• Conduct in-depth technical assessments across complex architectures and interdependent systems, distilling findings into clear, actionable recommendations for both technical and non-technical stakeholders
• Translate technical strategy into structured program plans, creating new program formats and frameworks that improve clarity, efficiency, and alignment across program teams and organizational leadership
• Identify, communicate, and prioritize program risks using quantitative methods, maintain detailed risk registers, and develop mitigation and contingency plans in partnership with cross-functional leadership
• Drive cross-organizational dependency management and alignment, proactively resolving conflicts and unblocking complex workstreams to maintain program momentum
• Craft and deliver technically complex communications tailored to diverse audiences, including engineering teams and organizational leaders, ensuring stakeholders have the context needed for effective decision-making
• Partner with organizational leaders to influence technical strategy and roadmap direction, incorporating inputs from engineering requirements, product quality signals, and operational efficiency considerations
• Establish and scale program management best practices, risk mitigation processes, and reporting frameworks that can be applied across multiple programs and teams
• Build and contribute to the TPM community through mentoring other TPMs, supporting hiring and onboarding, and representing the TPM function in organizational forums
• Proactively identify systemic issues slowing teams down, drive changes to address them, and facilitate resolution of technical problems that span multiple programs or organizations

Minimum Qualifications
• 10+ years of experience in technical program management, software engineering, or a related technical field, with demonstrated ownership of large-scale, cross-organizational programs
• Experience conducting deep technical assessments across complex, interdependent systems and translating findings into program strategy and stakeholder recommendations
• Experience building and managing program structures for cross-organizational programs, including risk registers, dependency tracking, and executive-level reporting and dashboards
• Experience influencing technical decisions and driving alignment across multiple engineering teams and organizational leaders through structured communication and stakeholder engagement
• Experience applying quantitative methods to evaluate and prioritize program risks, including timeline, scope, and business impact analysis

Preferred Qualifications
• Experience driving adoption of new technologies or architectural changes across large, distributed engineering organizations
• Experience scaling program management frameworks and best practices across a TPM organization or multiple product domains
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
• Experience mentoring other program managers and contributing to hiring, onboarding, or community-building initiatives within a TPM function
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)