Customer and Product Solutions Engineer, GenAI, Antigravity
Google· Internet & Cloud Services· Oct 6, 2026 · 21d ago
Sunnyvale, CA, USA
In office
Full-time
Mid
$100K–$130K est.
3+ years exp
Job description
In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration, and more).
In this role, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products. You will be the Google Engineer working with Google's ambitious Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.
To learn more about gTech, check out our video .
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $127000 - $182000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .
• Support Partner and product teams with their end to end data pipelines to leverage Google DeepMind Gen AI products and APIs.
• Partner directly with engineering product management to influence and shape product roadmaps and future direction.
• Help product teams make new releases and manage the release train.
• Troubleshoot issues and help partners resolve them. Build and maintain internal tools and solutions powered by Agentic toolkits and Gen AI offerings to enhance support workflows and partner enablement.
• Stay up-to-date on the latest advancements in Gen AI and related technologies, sharing knowledge and insights with the team and partners.
• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 3 years of experience working with client-side web technologies (e.g., HTML, CSS, JavaScript, or HTTP).
• 3 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
• Experience troubleshooting technical issues for internal/external partners or customers.
Minimum qualifications:
• Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
• 3 years of experience working with client-side web technologies (e.g., HTML, CSS, JavaScript, or HTTP).
• 3 years of experience coding with one or more programming languages (e.g., Java, C/C++, Python).
• Experience troubleshooting technical issues for internal/external partners or customers.
Preferred qualifications:
• Master’s degree in Engineering, Computer Science, Business, or a related field.
• Experience in an analytical role such as business intelligence, data analytics, or statistics.
• Experience working with database technologies (e.g., SQL, NoSQL).
• Experience with cloud technologies such as architecting, developing, or maintaining cloud solutions in virtualized environments or cloud data engineering.
• Experience using machine learning and building solutions.
• Experience working with systems (e.g., Linux, Unix, Windows).
Application prep
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Keywords to mirror
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