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About the job
In this role, you will drive accelerated business growth for Google Cloud through Tensor Processing Unit (TPU) or Graphics Processing Unit (GPU) partnerships and customer engagements across the Google Cloud Platform (GCP) Go-To-Market (GTM) segments and verticals. Your leadership role will require collaboration with AI Infrastructure tech specialists and field business, capacity, product, engineering, and finance teams to develop and grow AI Infrastructure TPU/GPU partnerships and operate at the C-level internally and externally.
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 $176,000-$245,000 + 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
- Drive and grow the AI Infra business for Google Cloud through new, expanded, or accelerated TPU/GPU partnerships and customer engagements across GCP’s GTM segments.
- Drive GTM and business initiatives to accelerate growth for Google Cloud TPU/GPU business.
- Develop and implement regional or industry-specific GTM strategies jointly with the AI Infrastructure team in cross-functional collaboration.
- Build trusted relationships with the C-suite of GCP’s AI Infrastructure customers, collaborate on the direction, and serve as a business partner.
- Serve as thought leader and advisor to Google Cloud’s executive management and represent Google Cloud externally in industry, customer, and partner events.
Minimum qualifications
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Bachelor's degree or equivalent practical experience.
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12 years of experience in enterprise technology or cloud sales, partner management, and business development and strategy.
management and business development and strategy. -
Experience leading agreements, requiring cross-functional coordination and C-suite management.
Preferred qualifications
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MBA degree.
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Experience working across multiple organizations to drive initiatives to resolution.
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Experience in business development, consulting, or business in the technology industry, promoting Platform-as-a-Service (PaaS) or Infrastructure-as-a-Service (IaaS).
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Experience operating in a fluid work environment along with excellent communication skills.
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Knowledge of AI natives with an understanding of the emerging generative AI industry tech stack.
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Understanding of GCP’s AI infrastructure and agreement cycles.
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About Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
Employees
Mountain View
Headquarters
$1,700B
Valuation
Reviews
3.7
25 reviews
Work-life balance
3.8
Compensation
4.2
Culture
3.4
Career
3.9
Management
2.8
68%
Recommend to a friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
Cons
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
Salary Ranges
57,502 data points
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0 reports
$176,704
total per year
Base
-
Stock
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Bonus
-
$150,298
$203,110
Interview experience
9 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Offer rate
44%
Experience
Positive 0%
Neutral 56%
Negative 44%
Interview process
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
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