Align cross-functionally with Field Sales Representatives (FSRs) and Partners to execute joint Data and AI sales plays to scale success and GCP data adoption, driving platform standardization and co-sell motions.
Synthesize customer friction points and cross-product gaps into authoritative engineering requirements to shape and protect Google's unified Data and AI narrative.
Align cross-functionally with Field Sales Representatives (FSRs) and Partners to execute joint Data and AI sales plays to scale success and GCP data adoption, driving platform standardization and co-sell motions.
Act as a product catalyst, identifying repeatable field patterns and technical friction points in Google’s AI stack and converting them into reusable modules or product feature requests for engineering teams.
Conduct workload performance profiling, workload migration, and optimization of large-scale training and inference models and data pipelines specifically for Google Cloud TPU hardware topologies (e.g., 3D Torus over Inter-Chip Interconnect and Optical Circuit Switches).
Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
Identify repeatable field patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for engineering teams.
Embed with customer's staff engineers and leaders to identify core SDLC bottlenecks, such as legacy migrations, test coverage, review latency, or onboarding friction, and define success metrics.