Staff Software Engineer, Infra, Ads Quality Infrastructure, Dynamo, Google Ads

About the role

MINIMUM QUALIFICATIONS:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience building and developing large-scale infrastructure,

distributed systems or networks, or experience with compute technologies,

storage, or hardware architecture.

• Experience designing, building, and operating large-scale distributed

systems, with a focus on scalability, fault tolerance, and reliability.

• Experience in low-level systems programming languages (e.g., C++ or C).
• Experience designing and implementing infrastructure solutions.

PREFERRED QUALIFICATIONS:

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

technical field.

• 3 years of experience in a technical leadership role leading project teams

and setting technical direction.

• Experience in C++ and distributed backend systems architecting solutions that

process massive datasets at low latency.

• Experience building data extraction and transformation platforms or working

with machine learning infrastructure.

• Experience working across engineering domains including e-commerce, shopping,

or digital advertising.

• Experience modernizing legacy architecture, driving migrations, and ensuring

production reliability with cross-functional partner teams.

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.

Google Ads is at the forefront of AI innovation, applying cutting-edge machine

learning and Generative AI models like Gemini to power a multi-billion dollar

global business.

Our work directly impacts billions of users by protecting users from harm,

improving ad quality, and optimizing campaigns for advertiser

return-on-investment. We foster a culture of deep collaboration, partnering

closely with teams like Google Research and DeepMind to solve complex

challenges. Join us to work on state-of-the-art AI, take on problems at an

unparalleled scale, and build the next generation of advertising technology.

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:

• Lead architectural improvements for next-generation incremental data

infrastructure, focusing on reducing system complexity and improving

reliability.

• Design and build highly scalable systems, architecting distributed data

processing pipelines that extract and transform massive datasets to power

advertising serving systems.

• Drive software engineering best practices and system design while mentoring

team members and ensuring production health.

• Develop and scale frameworks that support artificial intelligence and machine

learning workloads, including offline embedding generation and model

inference.

• Partner with cross-functional teams to optimize how product and offer

metadata is indexed and served with low latency.