Own end-to-end analytics engineering for AI and developer-experience telemetry, including instrumentation, production pipelines, governed metrics, monitoring, executive dashboards, and analysis. Define and validate new measures of AI productivity and ROI, communicate findings to senior stakeholders, and recommend improvements to tooling, processes, and investment. Collaborate with data engineering, applied AI, and data science teams while using AI coding agents to build and maintain pipelines and reporting.

Provides strategic and administrative partnership to senior executives, managing calendars, travel, expenses, operating rhythms, meetings, information flow, and follow-through. Improves workflows through AI, automation, documentation, reporting, and scalable systems. Builds cross-functional relationships, supports executive programs and planning processes, mentors peers, and helps strengthen centralized Executive Operations practices. Principal-level candidates also architect support models, lead process improvements, and coach executive support professionals.

Build and own foundational Android platform infrastructure, including architecture, shared libraries, developer tooling, observability, performance, and experimentation systems. Lead AI-native engineering practices, evaluate AI development tools, and drive cross-organizational technical initiatives. Partner across engineering, product, and design; establish scalable standards; identify systemic risks; communicate architectural tradeoffs; and mentor Android engineers across the organization.