In this role, you will be at the forefront of leading Google's data and generative AI to solve real-world issues for customers. You will act as a partner in tandem with key customers, working to build, deploy, and optimize sophisticated Data and AI agents and solutions leveraging Google’s first-class technologies. You will bridge the gap between powerful platform primitives and the cohesive, high-value solution enterprise demand. You will also bridge the gap between our core product engineering teams and customer needs. You will directly accelerate product innovation, customer success, disrupt the traditional Software Development Life-Cycle (SDLC), and shape the future of our Data and AI products.
You will operate on a "Co-Invest, Build, Codify" flywheel. You will embed with a select group of lighthouse customers to co-develop breakthrough solutions in real-world environments; rather than stopping at individual customer success, your primary mandate is to translate these engagements into scalable assets, delivering validated product prototypes to engineering and repeatable go-to-market blueprints to the field.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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $183000 - $266000 (USD) + 20% bonus target + bonus + equity + benefits
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benefits at Google.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 7 years of experience in software engineering, solution architecture, or technical consulting.
- 2 years of experience with generative AI techniques (e.g., LLMs, multimodal, large vision models) or with generative AI-related concepts (e.g., language modeling, computer vision).
- Experience writing production-level code in one or more programming languages.
Preferred qualifications:
- 10 years of experience in software engineering, solution architecture, or technical consulting.
- 6 years of experience designing and deploying cloud-native distributed systems, data pipelines, or AI/ML workflows in an enterprise environment.
- 3 years of experience with SQL and modern data warehousing concepts.
- 1 year of experience in prompt developing, model evaluation, and the creative application of AI.