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Open nowFirst seen 5 hours ago

Senior Engineer, AI Productivity Team

Google3,180 open roles

Where
São Paulo, Brazil
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Your applicationOpen nowSenior Engineer, AI Productivity TeamGoogle · São Paulo, Brazil

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

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The clock on this job

Early applications get read.

13.3% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 29 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.6%3 days
  3. 13.3%7 days
  4. 21.3%14 days
  5. 35.7%30 days
  6. 59.1%60 days
This job: first seen 5 hours ago

Google median: 29 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Please submit your resume in English - we can only consider applications submitted in this language.

Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 5 years of experience designing, building, and operating large-scale distributed systems, with a focus on scalability, fault tolerance, and reliability.
  • Experience in a technical leadership role, overseeing projects and managing engineers.
  • Experience with system design, system architecture, distributed systems, software engineering, and full-stack development.
  • Experience building developer tools to improve development velocity, code quality, or code health (e.g., CI/CD, compilers, test automation frameworks).
  • Experience with one or more programming or scripting languages (e.g., Python, Go, Java, C++, Bash, Groovy).

Preferred qualifications:

  • Experience with Large Language Models (LLMs), Agentic Architectures (ADK, Orcas, Agency), Distributed Systems, Compilers/AST Analysis, SQL & Database Internals.
  • Proven track record of designing and maintaining high-scale distributed systems, APIs, or developer platforms in Python and TypeScript.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

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.

Responsibilities

  • Define multi-quarter roadmaps for emerging AI productivity initiatives. Align platform capabilities with business strategic priorities and evolving LLM infrastructure.
  • Lead end-to-end design reviews for high-throughput distributed systems. Architect secure, scalable integrations across agent frameworks and large-scale data engines.
  • Set high standards for system reliability, test automation, and code health. Establish rigorous SLOs and automated evaluation baselines to measure platform accuracy, latency, and quota utilization.
  • Serve as a technical advisor to internal partner teams, AI researchers, and developer communities. Translate developer feedback into scalable platform features and standardized API agreements.
  • Embed robust Privacy, Safety, and Security (PSS) principles into agent profiling, synthetic eval generation, and in-SQL model execution.
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