Ecosystem Engineering Lead, AI and AI Platforms, Google Cloud

Google•Kirkland, WA

3d•$233,000 - $324,000

About The Position

The Google Cloud Platform team helps customers transform their businesses with cloud technology. Its products are built for security, reliability, and scalability, spanning infrastructure, applications, devices, and hardware. In this role, you will lead a dedicated team focused on AI and Agentic AI Platforms and serve as a Generative AI subject matter expert. You will collaborate with partners, Product Development, and Technical Sales to deliver Google Cloud AI products. You will help prospective customers and partners understand Google AI, explain technical features, design architectures, build AI-powered applications, and troubleshoot challenges. You will also guide partners in using Google Cloud Generative AI services, including Large Language Models, Agent Platforms, tooling, and Google-developed Tensor Processing Units. The role includes advising partner executives on AI roadmaps, identifying use cases and business opportunities, and working across teams to deliver solutions and support partner success.

Requirements

Bachelor’s degree in Computer Science, Technology, Engineering, Mathematics, or equivalent practical experience.
10 years of experience serving as a technical Solution Architect in a cloud computing environment in customer- or partner-facing roles.
5 years of experience with Large Language Models (LLMs), Agentic frameworks, Agentic workflows, Open Source, Big Data, Machine Learning, and numerical programming frameworks.
5 years of experience with AI products, technologies, and infrastructure.
Experience bridging technical implementation with business strategy, such as in a Partner Architect, Technical PM, or Principal Consultant role.

Nice To Haves

Master's degree in Computer Science or a related technical field.
Experience architecting and developing software or infrastructure for scalable, distributed systems with ML technologies.
Experience building AI and ML solutions, operation frameworks such as Kubeflow, and leveraging specific ML architectures.
Understanding of AI Models, Large Language Models, AI agents, AI Agentic workflows, AI specialized infrastructure, and responsible AI practices.
Ability to lead cross-functional teams and deliver end-to-end solutions to customers and partners.
Ability to quickly learn, understand, and work with emerging technologies, methodologies, and solutions, including leading a team of Ecosystem Engineers.

Responsibilities

Serve as a trusted technical advisor to partner executive leadership, including CTOs and Chief Product Officers, aligning multiyear AI roadmaps and exploring advanced technical possibilities.
Lead AI and agentic activities with strategic partners, including executive briefings, ideation, identification of priority use cases, conversion, and comprehensive value realization with Google AI and Agentic platforms.
Identify and qualify business opportunities with partners, understand key technical objections, and lead multidisciplinary teams to deliver proof of concepts, custom solution demos, and Generative AI joint innovation.
Partner with product management, engineering, solution management, and Customer Engineering teams to enable partner success, helping developers, creators, and enterprises build products using Google Generative Language APIs.
Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement and deploy complete, robust solutions using Google Cloud best practices.