Technical Program Manager, Risk Organization

You will be responsible for driving risk programs end to end, from identifying and assessing emerging risks through the design, implementation, and sustained operation of controls and safeguards. This includes developing and refining repeatable frameworks for risk assessment, mitigation, and evidence of effectiveness, ensuring robust and predictable execution, and proactively resolving technical and organizational challenges to maintain program momentum.

You will use your problem-solving, technical acumen, and business insight to scale how risk is identified, mitigated, and demonstrably managed across Meta's products and infrastructure. You will communicate transparently across all levels, motivate multidisciplinary teams, and champion best practices to deliver durable, auditable outcomes that reduce risk and strengthen trust in Meta's systems.

Responsibilities

Establish and lead effective program teams to ensure alignment and achieve common objectives Work closely with engineering, product, legal, policy, and compliance stakeholders to define program requirements, prioritize initiatives, and establish scope, including shaping the roadmap and long-term strategy for partner teams Create and implement communication strategies to proactively share program status, challenges, and risks with stakeholders Drive successful outcomes by actively managing cross-functional dependencies, mitigating risks, and adjusting scope, timeline, and resources as needed Collaborate with cross-functional teams to lead the end-to-end lifecycle of programs, including technical analysis, design, development, testing, implementation, and post-launch support Establish and track key metrics, quality benchmarks, and performance indicators to drive accountability and ensure effective cross-functional execution Anticipate and evaluate complex, long-term risk and compliance challenges in close partnership with engineering leaders and key stakeholders Drive product strategy to support and align with key company initiatives Lead process improvements across internal and external teams, streamlining workflows and reducing manual effort through automation

Qualifications

BS in EE, CS, ME, or related technical field, or equivalent experience 12+ years in software engineering, hardware engineering, systems engineering, or technical product/program management Knowledge of software and hardware development for large-scale hardware readiness, including end-to-end product development processes Excel at clearly communicating complex technical investments simply and understandably Experience delivering complex technology programs and products from inception through successful delivery Knowledge of understanding user needs, gathering requirements, defining project scope Experience working under own initiative across multiple teams, with critical thinking and thought leadership in ambiguous spaces Experience defining and optimizing engineering processes at scale Experience building cross-functional relationships and navigating complex challenges Experience analyzing and solving complex technical problems in large-scale systems (root cause analysis, capacity planning, system design trade-offs, risk assessment) Experience building relationships across multi-disciplinary teams and partners in different time zones Experience defining strategic direction and identifying new opportunities for impact across products, platforms, programs Experience communicating at the executive level and influencing leadership and technical management teams Knowledge of Large Language Models, machine learning, and scaling distributed systems Knowledge of privacy, security, or regulatory compliance domains and how they apply to large-scale systems (keep the original instead if this role covers AI risk) Demonstrated experience in identifying new opportunities for the larger organization and influencing stakeholders Proven commitment to scaling risk management and infrastructure for large-scale AI distributed compute systems Ongoing AI skill development (prompt/context engineering, agent orchestration) and staying current with emerging AI tech Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies Adhering to and implementing responsible, ethical AI practices (risk assessment, bias mitigation, quality/accuracy reviews) Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements) Integrating AI tools to optimize/redesign workflows with measurable impact Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews) Communicating complex technical investments clearly to executive and cross-functional stakeholders Knowledge of regulatory or audit environments and evidence-based assurance practices