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Salary
≈ $119k – $231k per year (Estimated)
Location
In office (New York)
Seniority
Staff · 2+ years exp

Confirmed on the employer's own hiring board on Oct 1, 2026. First seen by Alion on Sep 28, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.

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: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Improve, maintain (including debug) and run machine learning/optimization models and other advanced analytical tools to centralize energy and power delivery and support energy agreement due diligence.
  • Collaborating on ETL data pipelines, building predictive and optimization models, implementing tooling visualization/application, configuration for deployment.
  • Scale Minimum Viable Product (MVPs) into production systems and work with software engineers to harden prototypes into production-grade solutions - establishing the testing, monitoring, code quality, and deployment standards then manage execution through to launch.
  • Rapid AI prototyping with domain experts directly with energy and data center domain experts to rapidly prototype AI-enabled solutions, using their expertise to shape the problem framing and validate outputs.
  • Coordinate cross-functional stakeholder groups to make decisions about data, feature requests, model development and give updates on ongoing work stream and key milestones.

Qualifications

Minimum qualifications:

  • Bachelor's degree in a technical field, or equivalent practical experience.
  • 2 years of experience in program management.
  • 2 years of experience in energy industry.
  • 2 years of development experience in data engineering, data science, or application engineering.

Preferred qualifications:

  • Master's degree in Operations Research, Engineering, Economics, or a related quantitative field.
  • Experience in the energy sector - wholesale power markets, PPA/ESA structures, nodal pricing, load or price forecasting, storage economics, or carbon-free energy accounting.
  • Experience quickly building prototypes, and taking prototypes to production, including working with software engineers on testing, monitoring, and deployment standards.
  • Experience building full-stack analytics tooling, including data pipelines, backend services, and visualization or application front ends.
  • Ability to translate technical analysis into recommendations for executive and non-technical audiences.
  • Passionate about AI solutions and ability to quickly prototype to solve business challenges.
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