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Job Details
Posted date: Feb 20, 2026
Location: Seattle, WA
Level: Executive
Estimated salary: $354,000
Range: $294,000 - $414,000
Description
Drive AI model development for databases, collaborating closely with Google DeepMind and Cloud AI teams. Lead the technical direction of several teams covering the whole spectrum of AI powered databases. Oversee the development and deployment of AI models, including Natural Language Understanding (NLU), Natural Language Generation (NLG), and machine learning algorithms targeted towards database systems. Collaborate with engineering teams to integrate AI capabilities into existing and new database systems. Work closely with product management to define the product roadmap and ensure that GenAI is used to its full potential. Collaborate with designers to create user-friendly and intuitive database interfaces. Work with other stakeholders to ensure that GenAI-powered data analytics products are aligned with the company's overall business goals.Google Cloud Databases feature industry-leading AI capabilities such as the state-of-the-art ScaNN vector search, leading AI models for semantic reranking an AI Query Engine - all built-in and delivered through SQL. By developing state-of-the-art models and industry-leading AI capabilities in databases, Google Cloud is enabling customers to bring Enterprise AI to production on their real-time business data.
We are looking for Principal Engineer who will set and lead technical direction for teams of AI/ML engineers and scientists in the development and delivery of machine learning and Generative AI (genAI) powered database products and services. This role is critical in reimagining how Google’s foundation models can fundamentally improve in solving the most critical problems in data management.
You will drive innovation to build industry leading data capabilities across our database products including areas such as custom, task-specific models, and Applied AI across vector search, natural language interfaces to SQL, AI Agents, and AI functions in query processing.
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 $294,000-$414,000 + 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: Master's degree in Computer Science, Artificial Intelligence, a related field, or equivalent practical experience. 15 years of AI/ML experience building models and delivering AI in production. Experience with model training, evals, inference, AI infrastructure, Agents and unstructured data platforms (e.g., PyTorch, TensorFlow, JAX, Hugging Face, RAG (Retrieval-Augmented Generation), LoRA, PEFT, Quantization, vLLM, LangChain). Experience tracking industry trends and landscapes in AI and machine learning (Agentic AI, inference, training, etc.).Preferred qualifications: Experience in building state-of-the-art AI models, training, and post-training for custom models or foundation models. Experience with reinforcement learning. Experience collaborating across organizations and with cross-functional teams. Demonstrated ability to drive innovation and foster a culture of technical excellence. Excellent communication, people, and presentation skills, with the ability to articulate complex technical concepts to audiences. Strong product sensibility, with capability to convert and drive key product innovations and opportunities.