Strategic Partner Development Manager, AI Pureplay

Google · United States

Minimum Qualifications

• Bachelor's degree or equivalent practical experience.
  
• 15 years of experience in Partner Management, Business Development, Sales, or Channel Development in the technology industry.
• Experience participating in or coordinating AI/ML technical transformations, utilizing an Forward Deployed Engineer (FDE) or embedded delivery model.

Preferred Qualifications

• Experience launching partner products and solutions, including complex channel go-to-market motions such as multi-partner solutions, procurement through cloud marketplaces, and consumption-based solutions; experience planning and managing at strategic and operational levels.
• Experience managing and growing technology partnership relationships with cross-functional teams internally and externally.
• Experience interfacing with, and being a trusted partner for, C-level executives in partner companies.
• Proficiency with Google Cloud AI offerings (Vertex AI, Gemini, ADK) and familiarity with modern multi-agent systems (e.g., LangGraph, CrewAI), coding agents, and open-source developer tool harnesses.

Responsibilities

• Coordinate day-to-day operations of capacity planning models to match scarce, high-value partner Forward Deployed Engineer (FDE) resources with high-stakes customer accounts, track engagement pipelines, manage staffing models, and monitor delivery milestones to safeguard co-sell and delivery excellence.
• Support partner teams as they embed directly within enterprise accounts, helping them navigate complex customer environments and successfully bridge multi-agent orchestration with legacy corporate databases and hybrid architectures.
• Drive the ground-level execution of commercial structures that accelerate time-to-value and Return on Investment (ROI) for the customer, scale business for the partner, and maximize platform consumption for Google Cloud.
• Act as a critical touchpoint between partner engineers, Google Cloud Sales teams, and technology Leadership, gathering real-world field insights and technical bottlenecks directly from partner deployments, helping synthesizing feedback back to internal Cloud AI Product and Engineering teams.