About the role

What will you do at Google?

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.

* 8 years of experience with designing and implementing large-scale distributed

systems.

* 5 years of experience with machine learning (ML) infrastructure or another ML

field.

* Experience with architectural ownership for distributed systems or

infrastructure components.

* Experience building and deploying agentic AI systems.

PREFERRED QUALIFICATIONS:

* Master’s degree or PhD in Engineering, Computer Science, or a related

technical field.

* Experience managing rapid technical iteration, 0->1 innovation, and managing

deep technical ambiguity across multiple engineering organizations.

* Experience defining organization-wide technical strategies, establishing

engineering best practices, and mentoring Executive Engineers and Tech Leads.

* Background in Trust and Safety, content moderation, security, or anti-abuse

engineering at a global scale, managing billions of daily events or real-time

streaming data.

* Strong technical communication skills, with a proven ability to translate

complex architectural trade-offs and AI capabilities into recommendations for

cross-functional executives.

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.

In this role, you will

steer a high-performing engineering organization. You
will architect fault-tolerant, and horizontally scalable solutions across the
entire technical stack, ensuring user protection at Google scale.
You will grow in ambiguity, resolving cross-system friction and managing
systemic risk across complex distributed networks. You will act as a massive
multiplier: defining engineering standards, mentoring tech leads across the
organization, enforcing operational excellence and driving cross-functional
technical execution.
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
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Define, advocate, and execute the overarching Trust and Safety technology
roadmap, architecting next-generation AI/ML systems and highly reliable
distributed infrastructure to automate and scale global user protection.
* Oversee the integration of high-availability, low-latency production systems
with stringent Service Level Objective (SLO) guarantees, driving excellence
across system bottlenecks, data consistency, capacity planning, and
cost-efficiency.
* Steer critical, multi-team technical initiatives from initial abstract
discovery through to large-scale deployment, translating high-level business
goals into parallelizable engineering workstreams.
* Define standards for fault-tolerant architectures while mentoring Tech Leads
in industry best practices across code quality, CI/CD, comprehensive testing,
and systemic technical debt reduction.
* Partner closely with Product, Policy, and Data Science leadership to
co-create the global technology stack, serving as a trusted advisor to
executives and abstracting complex technical trade-offs for non-technical
stakeholders.

Which skills does this role require?

Distributed systemsMachine learningAgentic AISecurity engineeringSystem architectureTechnical leadershipData streamingLarge-scale system designSoftware engineeringCross-functional communicationOperational excellenceFault-tolerant architectureStaff Software EngineerDistributed SystemsMachine LearningInfrastructureSystem ArchitectureReal-time streamingFault-tolerantScalabilityCI/CDTechnical StrategyMentorshipData ScienceProduct ManagementEngineering StandardsSystemic RiskHigh-availabilityLow-latencyCapacity PlanningTechnical DebtCross-functional LeadershipProduct Strategy

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