Demonstrated proficiency using AI-enabled tools to build product artifacts at scale 10+ years of experience working collaboratively with engineering, design and user research teams 10+ years product management and/or Product Design Experience developing and championing AI-native strategies across organizations BA/BS in Computer Science or related field Seasoned Product Management experience shipping enterprise or platform products at scale Experience taking a 0-1 platform from strategy through enterprise adoption and full product lifecycle Experience turning diverse enterprise requirements and customer requests into a single coherent product strategy Experience with agentic harness and AI infra plus LLM evals: orchestration, tool use, golden datasets and judges, task completion measurement Technical depth with data and infra: analyze complex datasets, lead credible architecture tradeoff discussions on reasoning, latency, reliability, cost Communication and influence: radical clarity from exec to eng, AI-native builder who prototypes and ships with AI tools Shipped enterprise-grade AI infra or agentic products: harness, reliability, latency, security and auth, SLAs, readiness Redesigned workflows with AI tools to measurable impact on quality or task completion Worked with field, solutions, or partnerships teams on enterprise adoption 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. Own enterprise product readiness from pilot to scaled rollout: migration and rollout plans tracked with scorecards, privacy and compliance readiness (data retention, deletion, PII redaction, tenant isolation), and closure on reliability, auth, safety, and SLAs with engineering and field teams.