Director of AI Program Management & Execution

Socket.dev; Sunnyvale (CA); On-site; USD 281,000 - 391,000; Full time

Job summary

Google Cloud is seeking a senior leader to build and scale a Technical Program Management organization focused on AI-powered solutions. You will partner with engineering, product, and leadership to ensure alignment with priorities and drive outcomes across the Vertex fleet.

Responsibilities include lifecycle management of GPU/TPU resources, capacity planning, and advocating for efficient deployment strategies to maximize impact in a rapidly evolving AI landscape.

Qualifications

• 15 years of experience managing technical projects in cloud or AI-driven industries.
• 10 years of experience leading teams in technical program management or engineering management.
• Bachelor’s degree in Electrical or Computer Engineering or related field, or equivalent practical experience.
• Experience with Generative AI, Large Language Models, Agents, and AI Workflow tools.
• Experience leading capacity, utilization, efficiency, and model deployment efforts.

Responsibilities

• Lead, inspire, and build a healthy and scalable organization of Technical Program Managers.
• Partner with senior leadership, engineering, and product managers to align priorities.
• Oversee GPU/TPU resources lifecycle across multiple supply channels.
• Lead supply management for hardware types and integrate within the Vertex fleet.
• Drive allocation and resource utilization strategies to maximize fleet impact.

Skills

Technical program management

Team leadership

Generative AI

LLMs

AI workflow tools

Capacity planning

Model deployment

Education

Bachelor’s degree in Electrical or Computer Engineering

Job description

Google Cloud is seeking a senior leader to build and scale a Technical Program Management organization focused on AI-powered solutions. You will partner with engineering, product, and leadership to ensure alignment with priorities and drive outcomes across the Vertex fleet.

Responsibilities include lifecycle management of GPU/TPU resources, capacity planning, and advocating for efficient deployment strategies to maximize impact in a rapidly evolving AI landscape.