Jobs · Information Technology · Colorado

Principal Engineer, Resource Optimization and Fleet Logic

Google · Thornton, CO · 1 mo ago
On-siteInformation TechnologyFull-time
We need to output HTML fragment with sections: headings using

. Use
  • for lists. Use

    for prose. Do not repeat job title. No Job ID. Remove boilerplate: EEO, legal, accommodation, application instructions, etc. Keep substantive info: application window date, location options, minimum qualifications, preferred qualifications, about the job description, responsibilities, pay, benefits? Pay is given: "Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits". So we have pay and benefits mentioned. Benefits: mention "benefits" but not details; we can include a Benefits section with generic statement? The rule: never create Benefits section unless posting actually states them. It does state "+ equity + benefits". So we can include Benefits section with that statement. However we need to avoid filler like "varies". We have specific pay range and bonus target. So we can include Pay section with that. Benefits section can mention "equity + benefits" as per posting. Could also combine Pay and Benefits? Better separate. We need sections: About the role? The posting has "About The Job". That's a section heading. Use

    About The Job

    . Responsibilities: there is a "Responsibilities" heading after bullet list. Use

    Responsibilities

    . Requirements/Qualifications: we have Minimum qualifications and Preferred qualifications. Could combine into Requirements section? The rule: use headings for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have Minimum qualifications and Preferred qualifications. Could use

    Qualifications

    with subparts? But we need to follow instruction: use

    for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have Qualifications heading and inside we can have

    for minimum and preferred qualifications maybe as separate paragraphs or lists. Could also have Requirements heading but we have qualifications. Let's use Qualifications. We also have location info and application window date. Could be under About the role? Or maybe a short paragraph under a heading like "Details". But we only create headings when there is real specific content. We have location and date; could be part of About the Job? Might be better to have a short

    after the heading? The instruction: do not put Job ID/requisition numbers as headings — fold minor metadata into a short

    or drop it. So location and date can be a short paragraph maybe under a heading like "About the role"? But we already have About The Job heading. Could include location and date in that section as a paragraph before the description. We need to preserve all substantive information: application window date, location options, minimum qualifications, preferred qualifications, about the job description, responsibilities, pay, benefits. We must remove boilerplate: EEO, accommodation, legal, etc. Also remove "Learn more about benefits at Google ." maybe part of responsibilities? Actually that line appears before responsibilities: "Learn more about benefits at Google ." That's a link; we should remove as it's boilerplate/application instruction? It's not substantive; we can drop. Also remove "Google is proud to be an equal opportunity workplace..." etc. Now craft HTML. Structure:

    About The Job

    The application window will be open until at least September 29, 2026. This opportunity will remain online based on business needs which may be before or after the specified date. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Thornton, CO, USA; Atlanta, GA, USA; Austin, TX, USA; Sunnyvale, CA, USA.

    [Then the description about Google runs one of the largest computational fleets...]

    But we need to keep the description exactly as given (preserve all substantive information). Let's copy the paragraph after "About The Job". The text: "About The Job Google runs one of the largest computational fleets in the world, with compute, storage, networking and dedicated accelerators spread across all continents. As Principal Engineer, you will own the architectural outlook and end-to-end technical strategy for our global capacity planning ecosystem. You will serve as the primary technical authority for a challenge, knitting together complex planning constraints, optimization scenarios, and machine deployment workflows to get optimal capacity online in the shortest time. As the Principal Engineer, Resource Optimization and Fleet Logic, you will pioneer the technological vision for Google’s planetary-scale capacity planning and fleet optimization architecture. You will define the multi-year architectural path to orchestrate data center capacity planning, placement, supply planning, and fleet reconfiguration for ML, compute & storage demand —ultimately empowering our largest, most demanding internal and external AI/ML customers. 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." We need to ensure we keep that. Then Responsibilities section: after "Responsibilities Learn more about benefits at Google ." we need to drop the "Learn more about benefits at Google ." line. Then list responsibilities: - Lead the design and evolution of next generation global fleet planning, defining a multi-year engineering roadmap to deliver 10x more data center capacity with ML, compute & storage resources. - Leverage deep technical knowledge across the data center stack, spanning ML hardware (TPUs/GPUs), general compute, power, cooling, physical space, supply chain workflows, and network topology to model, forecast, and dynamically reconfigure fleet resources. - Partner across AI & Infrastructure organizations to define a unified capacity management product suite meeting AI training and inference for internal and external customers. - Integrate cutting-edge AI/ML, operations research, and advanced mathematical optimization into capacity planning workflows to compress capacity cycles, eliminate stranded capacity, and maximize data center utilization. - Collaborate with academic institutions and industry pioneers to anticipate technology trends. We'll put each as
  • . Qualifications section: Minimum qualifications and Preferred qualifications. Minimum qualifications: "Bachelor's degree in Computer Science or similar technical field, or equivalent practical experience. 15 years of experience as a software engineer. Experience delivering large-scale capacity planning, IaaS/PaaS solutions, or fleet management systems." Preferred qualifications: "Master's degree or PhD in Computer Science or a field related (e.g., Networking or Security Systems). Experience architecting, leading, and delivering large-scale capacity planning, combinatorial optimization, fleet management, or distributed infrastructure transformations from concept to deployment. Deep understanding of modern AI/ML infrastructure demands (TPU/GPU topologies, accelerators) with the ability to integrate AI-driven solutions. Ability to influence and lead without direct authority, building strong cross-organizational relationships across disparate teams (e.g., Hardware, Software, Supply Chain, and Product Management). Exceptional communication skills, and ability to articulate complex mathematical, economic, and architectural concepts to engineering leaders and executive business stakeholders." We can present as two paragraphs or two lists. Use

    for prose; could also use

    • for each bullet. Since they are sentences, we can use

      . Pay section: "Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits" We can put that in

      . Benefits section: Since pay line includes "+ equity + benefits", we could mention benefits as "Equity and benefits are included as part of compensation." But we should not invent. The posting says "+ equity + benefits". So we can have a Benefits section with that statement: "Equity and benefits are included as part of compensation." However that is somewhat inferring. Might be better to combine Pay and Benefits? But rule: never create Benefits section unless posting actually states them. It does state "+ equity + benefits". So we can have Benefits section with that exact phrase: "Equity + benefits are included as part of compensation." But we need to preserve the exact wording? The posting says "+ equity + benefits". We could output: "

      Equity + benefits are included as part of compensation.

      " That's preserving the idea but not exact. Maybe better to include the exact phrase: "

      US: $307000 - $427000 (USD) + 30% bonus target + equity + benefits

      " under Pay, and then Benefits section could be omitted because it's already covered. But rule says we can create Benefits section only if posting actually states them. It does state benefits as part of compensation line. Could we just not create a separate Benefits section and keep it under Pay? That would be fine; we would have Pay section that includes benefits mention. The instruction: "Prefer a few substantive sections over many thin ones." So we could combine Pay and Benefits into one Pay section that includes the benefits mention. That seems acceptable. Thus sections: About The Job, Responsibilities, Qualifications, Pay. We need to ensure we don't repeat job title. No headings for Job ID etc. Now produce HTML fragment. Let's craft:

      About The Job

      The application window will be open until at least September 29, 2026. This opportunity will remain online based on business needs which may be before or after the specified date. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Thornton, CO, USA; Atlanta, GA, USA; Austin, TX, USA; Sunnyvale, CA, USA.

      Google runs one of the largest computational fleets in the world, with compute, storage, networking and dedicated accelerators spread across all continents. As Principal Engineer, you will own the architectural outlook and end-to-end technical strategy for our global capacity planning ecosystem. You will serve as the primary technical authority for a challenge, knitting together complex planning constraints, optimization scenarios, and machine deployment workflows to get optimal capacity online in the shortest time. As the Principal Engineer, Resource Optimization and Fleet Logic, you will pioneer the technological vision for Google’s planetary-scale capacity planning and fleet optimization architecture. You will define the multi-year architectural path to orchestrate data center capacity planning, placement, supply planning, and fleet reconfiguration for ML, compute & storage demand —ultimately empowering our largest, most demanding internal and external AI/ML customers. 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

      • Lead the design and evolution of next generation global fleet planning, defining a multi-year engineering roadmap to deliver 10x more data center capacity with ML, compute & storage resources.
      • Leverage deep technical knowledge across the data center stack, spanning ML hardware (TPUs/GPUs), general compute, power, cooling, physical space, supply chain workflows, and network topology to model, forecast, and dynamically reconfigure fleet resources.
      • Partner across AI & Infrastructure organizations to define a unified capacity management product suite meeting AI training and inference for internal and external customers.
      • Integrate cutting-edge AI/ML, operations research, and advanced mathematical optimization into capacity planning workflows to compress capacity cycles, eliminate stranded capacity, and maximize data center utilization.
      • Collaborate with academic institutions and industry pioneers to anticipate technology trends.

      Qualifications

      Minimum qualifications: Bachelor's degree in Computer Science or similar technical field

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