New job, posted less than a week ago!
Job Details
Posted date: Mar 19, 2026
Location: Seattle, WA
Level: Director
Estimated salary: $279,500
Range: $234,000 - $325,000
Description
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.As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms or product partnerships.
You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.
In this role, you will be instrumental in helping partners build applications on Google Cloud by leveraging Vertex AI, Cloud AI, Gemini, and Google Cloud Marketplace. You will play a key role in building a rapidly growing business by understanding the needs of our emerging Independent Software Vendor (ISV) partners and helping to shape the future of their businesses. You will work as part of the AI/ML Center of Excellence (CoE), dedicated to the Springboard team and its partners, collaborating closely with product development and technical business teams as a Generative 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 cutting-edge 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.
Qualifications
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.