Applied AI and Commercial Operations Specialist
Google· enterprise· Internet & Cloud Services· Oct 13, 2026 · 15d ago
Atlanta, GA, USA · Seattle, WA, USA · San Francisco, CA, USA · Los Angeles, CA, USA · Sunnyvale, CA, USA · New York, NY, USA
In office
Full-time
Staff
$115K–$197K est.
8+ years exp
Job description
As a Cloud Infra & AI Agent Specialist, you will be at the forefront of integrating artificial intelligence into our core operational and analytical frameworks. You will own projects across four key pillars: Agentic tools engineering, demand forecasting, capacity planning, and performance management. You will embed yourself in the core operations of the business, identify the most impactful areas for AI tooling and automation, develop an implementation roadmap, and then execute. You will design custom agent frameworks, integrate them with GTM and capacity systems, and build workflow automation engines.
This role requires a blend of technical engineering and strategic business analysis to evaluate large datasets and systematize processes across the entire GTM organization and to do so leveraging AI tools and agents. You will work closely with leadership to provide actionable insights that influence multi-billion dollar infrastructure decisions, ensuring our supply of compute, storage, and AI chips perfectly aligns with customer demand and Gemini model usage.
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: $186000 - $269000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google .
• Architect, build, and deploy custom Agentic solutions to streamline complex operations and manual regional workflows.
• Partner with capacity planning to design, implement, and operate capacity allocations forums for Compute (CPU), Storage, and AI Chips (TPU/GPU), automating and scaling global signaling processes.
• Evaluate, audit, and optimize complex cross-functional GTM systems by embedding autonomous intelligence models and feedback loops directly into core infrastructure decision-making.
• Leverage first class machine learning and AI tools to automate demand forecasting. Use customer consumption & pipeline data to seize demand and make procurement decisions against those signals.
• Build and scale robust performance management systems and database platforms to track revenue-based metrics across data center revenue, sales regions, and demand forecasting.
• Bachelor's degree in Computer Science, Engineering, Finance, or equivalent practical experience.
• 8 years of experience in data analysis.
• Experience with Agentic programming or application development.
• Experience in data analytics tools and languages, including advanced SQL, BigQuery, Looker, or similar.
• Experience in cloud infrastructure, including IaaS compute, storage, and networking products.
Minimum qualifications:
• Bachelor's degree in Computer Science, Engineering, Finance, or equivalent practical experience.
• 8 years of experience in data analysis.
• Experience with Agentic programming or application development.
• Experience in data analytics tools and languages, including advanced SQL, BigQuery, Looker, or similar.
• Experience in cloud infrastructure, including IaaS compute, storage, and networking products.
Preferred qualifications:
• Master’s degree or PhD in a quantitative field such as Engineering, Statistics, Business, or Mathematics.
• Experience building and deploying AI Agents or LLM-based applications in a production environment.
• Deep understanding of data center capacity planning concepts, including AI chip types (GPU/TPU) and hardware-level metrics.
• Demonstrated ability to build consensus across teams and manage competing interests across senior stakeholders; presenting and leading executive reviews.
• Demonstrated ability to operate in an unstructured environment and bring clarity through structured platforms and automated systems.
Application prep
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