About the job

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, the team embeds deeply with a select group of lighthouse customers to co-develop breakthrough solutions in real-world environments, rather than stopping at individual customer success, the team’s 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 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 $183,000-$265,000 + 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

• Act as the lead technical architect for incubation projects, while working to stitch Google’s Data and AI primitives (e.g., Vertex AI, Big Query, Gemini) into high-value solutions like agentic workflows and new solutions.

• Own the resolution of ambiguous hurdles that prevent adoption and debug integration issues, optimize inference latency, and architect security layers to turn "demos" into production-ready assets.

• Drive the "codify" phase by transforming bespoke solutions into reusable assets, author "golden path" code repositories and reference architectures to enable the broader ecosystem to scale your work.

• Provide direction and mentorship to the squad’s builder engineers, while establishing coding standards, review architectural designs, and ensure the team delivers high-quality, secure software.

• Partner with customer chief technology officers (CTOs) and chief data officers to validate technical feasibility and align our proposed architectures with their existing enterprise stacks.

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.