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Technical Program Manager, AI Agent Prototyper, Supply Chain

Google

Technical Program Manager, AI Agent Prototyper, Supply Chain

Google

·

On-site

·

Full-time

·

1w ago

  • Analyze and document business requirements for AI-driven solutions, ensuring an understanding of the problem space and desired outcomes.

  • Design, build, and prototype AI agents focused on optimizing key supply chain functions for cloud compute infrastructure (e.g., forecasting, capacity planning, demand sensing, component procurement, logistics, and reverse logistics).

  • Collaborate with data science and data engineering teams to identify, clean, and structure the necessary supply chain data for use in ML and agent models.

  • Partner closely with supply chain operations, architects, finance, and engineering teams to define requirements, gather feedback, and ensure prototypes align with strategic business objectives and drive user adoption in production.

  • Lead, mentor, and grow a technical program management team, fostering high performance and collaboration. Manage hiring, performance, career development, and resource allocation.

Google's projects, like our users, span the globe and require managers to keep the big picture in focus while being able to dive into the unique engineering challenges we face daily. As a Technical Program Manager at Google, you lead complex, multi-disciplinary engineering projects using your engineering expertise. You plan requirements with internal customers and usher projects through the entire project lifecycle. This includes managing project schedules, identifying risks and clearly communicating them to project stakeholders. You're equally at home explaining your team's analyses and recommendations to executives as you are discussing the technical trade-offs in product development with engineers.

Using your extensive technical and leadership expertise, you manage various Engineering-specific programs and teams.

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.

  • Bachelor's degree in Computer Science, Engineering, Mathematics, Operations Research, a related quantitative field, or equivalent practical experience.

  • 8 years of experience in global supply chain operations, planning, or logistics, within the enterprise hardware or cloud infrastructure space.

  • 5 years of experience in leadership roles with/without direct reports.

  • Experience with prompt engineering and classical ML solutions, predictive modeling, or deep learning solutions.

  • Experience working with generative AI, integrating genAI solutions into business processes, and agent-based modeling.

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About Google

Google

Google

Public

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

L9

Mid/L4

Principal/L7

Senior/L5

Staff/L6

VP

Intern

Director

Junior/L3 · Associate Product Manager 2 (APM2)

0 reports

$183,233

total per year

Base

-

Stock

-

Bonus

-

$155,748

$210,718

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