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.

The Google Advertising Platform powers multiple products, front ends, and teams. It guarantees the security and integrity of advertiser data at all times. Its query layer has the flexibility to handle around 10 million different variants of queries and leverages the power of storage systems that operate at petascale in order to manage massive amounts of advertiser data. It does all of this while conforming to strict latency guidelines that ensure a consistent, fast experience for advertisers.

The Ads Platform Engineering Productivity team is focused on accelerating developer velocity and hardening product quality. We do this by partnering closely with Ads Platform infrastructure and feature teams to build tooling, automation, scalable validation and release infrastructure, and driving quality insights and best practices into the development process.

Google Ads is helping power the open internet with the best technology that connects and creates value for people, publishers, advertisers, and Google. We’re made up of multiple teams, building Google’s Advertising products including search, display, shopping, travel and video advertising, as well as analytics. Our teams create trusted experiences between people and businesses with useful ads. We help grow businesses of all sizes from small businesses, to large brands, to YouTube creators, with effective advertiser tools that deliver measurable results. We also enable Google to engage with customers at scale.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Work with engineering partner teams to solve technical problems that enable feature teams to ship quality code at high velocity.

• Align with engineering partners and key stakeholders to define project deliverables and drive execution.

• Create the next generation developer tooling and infrastructure, focusing on productivity, continuous development, test infrastructure, and release automation while balancing the needs of developers using existing tools and frameworks.

• Own, develop and execute on long term strategy, roadmap and technical direction to improve quality, reliability and adoption of our tooling and infrastructure across the organization.

• Drive adoption of best practices in code health, testing, and maintainability.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 2 years of experience with software development in C++, Python, or Java programming languages.

• 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

• Experience in engineering productivity, developer tools, test automation, test automation framework.

Preferred qualifications

• Master's degree or PhD in Computer Science or a related technical field.

• 2 years of experience with data structures and algorithms.

• Experience developing accessible technologies.

• Experience in Generative AI.

• Experience with integration testing.