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Open nowFirst seen 5 hours ago

AI Sales Specialist, Google Cloud

Google3,444 open roles

Where
Sydney NSW, Australia; Melbourne VIC, Australia
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Your applicationOpen nowAI Sales Specialist, Google CloudGoogle · Sydney NSW, Australia; Melbourne VIC, Australia

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

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The clock on this job

Early applications get read.

12.7% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.5%3 days
  3. 12.7%7 days
  4. 20.4%14 days
  5. 35.6%30 days
  6. 58.7%60 days
This job: first seen 5 hours ago

Google median: 29 days open

The posting

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience in enterprise technology sales.
  • 3 years of experience in cloud, data, analytics, or AI/ML.

Preferred qualifications:

  • Experience selling Large Language Models (LLMs), agents, or generative technologies.
  • Experience in the regulatory and operational data challenges of specific industries (e.g., FSI, Retail, Telco, Manufacturing).
  • Experience working at a cloud provider, system integrator, or AI-native firm.
  • Ability to build business cases involving complex consumption economics.
  • Ability to explain AI agents, Retrieval-Augmented Generation (RAG), fine-tuning, vector search, and inference scaling and why they matter to business audiences.
  • Ability to plan territories, perform stakeholder mapping, and execute complex, multi-stage agreement cycles.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As an AI Sales Specialist, you will lead the enterprise transition from AI exploration to strategic production. You will sit at the intersection of technical depth and commercial strategy, helping customers navigate the journey from initial pilots to scalable systems that generate measurable Return on Investment (ROI).

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.

Responsibilities

  • Guide customers through the pilot-to-production journey. Distinguish between model Application Programming Interfaces (API) and full platform value, and drive scalable decisions.
  • Shift conversations to business cases. Model and platform Total Cost of Ownership (TCO), explain inference cost scaling, and articulate the ROI of build versus buy decisions.
  • Navigate the value patterns such as business generation (e.g., customer experience), efficiency (e.g., automation), and decision augmentation (e.g., insight).
  • Position AI agents within the context of the industry. Explain how data proximity, governance, and operational coherence (e.g., MLOps) on Vertex AI create a engaged advantage.
  • Leverage a team of Field Sales Representative (FSR) and Customer Engineers, and activate partners to scale industry-specific plays and accelerate implementation. Assess agreement maturity. Commit to defendable numbers based on technical reality and executive sponsorship.
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