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Software Engineer Manager, AI Systems and Intelligence Engine

Google
Posted 8 hours ago, valid for 12 days
Location

New York, NY, US

Salary

$207,000 - $300,000 per year

Contract type

Full Time

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Minimum qualifications:

  • Bachelor’s degree, or equivalent practical experience.
  • 8 years of experience in software development.
  • 3 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
  • 3 years of experience in a technical leadership role.
  • 2 years of experience in a people management or team leadership role.

Preferred qualifications:

  • Master's degree or PhD in Computer Science, or a related technical field.
  • 3 years of experience working in a complex, matrixed organization.
  • Experience in data pipelines, analysis, visualization, and insights generation.
  • Passion for acquiring knowledge in the domain of metrics and insights development.

About the job:

Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.

With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

The AI Systems Knowledge and Intelligence Engine (ASKIE) team architects the foundational intelligence layer for Google's agentic ecosystem, engineering the data, insights, and feedback loops that empower developers and autonomous agents. Our mission is to transform these insights into high-leverage, data-driven metrics and insights that empower leaders to make smarter decisions, ultimately shaping our AI native future, developer tools, productivity, and culture across Google and Alphabet.

The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

  • Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  • Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  • Develop the mid-term technical outlook and roadmap within the scope of your (often multiple) team(s). Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  • Design, guide and vet systems designs within the scope of the broader area, and write product or system development code to solve ambiguous problems.
  • Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).



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