Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience Experience utilizing data and analysis to explain technical problems and provide detailed feedback and solutions Demonstrated experience driving change within an organization and leading complex technical projects 8+ years of programming experience in a relevant language OR 4+ years experience with a PhD Experience architecting and deploying large-scale software systems, including taking complex AI applications from early prototypes to enterprise-ready production Experience architecting and scaling GenAI infrastructure across major cloud platforms (e.g., AWS, GCP), leveraging advanced cloud services (compute, distributed storage, ML frameworks) to optimize model performance, manage compute costs, and ensure enterprise-grade reliability Experience designing and implementing advanced AI testing systems (e.g., automated evaluation loops to proactively catch hallucinations, reasoning gaps, or safety issues in live products) Experience in regulated industries (financial services, insurance, healthcare) or navigating enterprise compliance requirements (SOC2, data residency, privacy frameworks) Demonstrated ability to lead technical engagements with external engineering teams (e.g., Forward Deployed Engineering, Solutions Architecture) and translate complex business constraints into robust system designs Demonstrated ability to act as a technical bridge between field deployments and internal engineering, using hands-on customer insights to directly shape core product and platform roadmaps 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 technologiesMeta builds technologies that help people connect, find communities, and grow businesses. Crucially, you'll take the friction you encounter in the field-like optimizing inference speeds, resolving interoperability issues, and connecting complex external data sources-and turn it into concrete technical proposals.