About the job

The Google Cloud Platform team helps customers transform and build what's next for their business all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers, developers, small and large businesses, educational institutions and government agencies see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

The Google Cloud Springboard team Recruits and On-boards emerging Generative AI ISV Start-Ups to Build and Deploy their products on Google Cloud. These ISVs will be new to the Google Cloud Infrastructure and Vertex AI Platforms. The Springboard team is dedicated to helping these ISVs build their application on Google Cloud and in particular to leverage Google Cloud Vertex AI Platform, Cloud AI, Gemini, Data Analytics and Google Cloud Marketplace. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our Emerging ISV Partners and help shape the future of their businesses. As a Generative AI Specialist for Global Partner Engineering, you will be dedicated to the Springboard team and Startup Partners. You will work with Product Development and Technical Sales teams as an Generative Artificial Intelligence (AI) subject matter expert.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

The US base salary range for this full-time position is $234,000-$325,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Work with ISV startup partners to identify business opportunities, understand key technical objections, and develop strategies to resolve technical blockers.

• Guide partners in the Springboard program to develop and deploy solutions on Google Cloud, recommending optimal integration strategies, enterprise architectures, and application infrastructure using best practices.

• Provide AI expertise to support technical relationships with partners by delivering product briefings, solution demos, and proof-of-concept work.

• Partner directly with Product Management to prioritize features and solutions that accelerate partner and customer adoption of Google Cloud's AI capabilities.

• Drive technical thought leadership by conducting quarterly workshops and webinars for ISVs, sharing roadmap updates, and authoring community blogs on AI advancements.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 10 years of experience serving in the capacity of a technical solution architect in a cloud computing environment in customer-partner facing roles.

• 5 years of experience with enterprise applications in the role of technical architect or implementation lead.

• Experience with technology including AI/ML and data.

Preferred qualifications

• Master's degree in Computer Science or a related technical field.

• Certifications in Google Cloud (e.g., Machine Learning Engineer).

• Experience as a customer-facing architect, developing scalable systems and AI-focused cloud infrastructure.

• Experience building AI/ML solutions using MLOps (e.g., Kubeflow) and deep learning architectures, Long Short-Term Memory (LSTM), etc.

• Understanding of AI models, agents, and the agentic workflow ecosystem (e.g., ADK, other frameworks, measurement, tool calling, A2A), alongside specialized infrastructure with insight into industry trends and responsible practices.