Software Engineer, Search Ads in AI Experiences

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.

As a key member of a small and versatile team, you design, test, deploy and maintain software solutions.

The Ads in AI Experiences team is responsible for one of the highest-priority initiatives at Google: reinventing Search Ads for the AI era (AI Overview, AI Mode). We are building the tech stack, the user experience, and the business model simultaneously. Our mission is to ensure that, as the Search experience evolves with AI, we unlock new ways for users to discover and engage with businesses through seamless, next-generation commercial experiences. We are a team of risk-takers and builders, responsible for experimenting with rapid velocity to define the next decade of Google’s business engine.

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

US: $123000 - $174000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Write clean, highly efficient, and well-tested code in C++, Java, or Python to support real-time offer verification, commercial fact-checking pipelines, and inventory grounding.
• Participate in factuality quality hill-climbing sprints by evaluating automated LLM-as-a-Rater verification outputs, diagnosing offer mismatch discrepancies, and refining precision heuristics.
• Implement ML feature pipelines and backend integrations that empower Search, Assistant, and Gemini surfaces to accurately corroborate commercial claims against authoritative merchant feeds.
• Partner with executive corroboration modeling leads and cross-functional teammates to rapidly triage verification latency errors, optimize factual accuracy, and sustain high sprint development velocity.
• Architect Google's presentation and rendering pipelines to write code that enables Search, Assistant, and Gemini surfaces to render multi-modal ad formats, partnering with technical leads and multi-disciplinary mentors to directly improve visual ad quality and user delight.
  

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
• 1 year of experience with data structures and algorithms.
• 1 year of experience implementing core ML concepts.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• 1 year of software development experience working on high-throughput backend applications, information verification pipelines, or machine learning feature systems.
• Experience developing accessible technologies.
• Demonstrated proficiency in modern programming languages (C++, Java, or Python) and foundational understanding of commercial grounding, multi-modal AI systems, or online advertising platforms.
• Proven track record of proactive engineering teamwork, debugging habits, and executing iterative quality improvement cycles in changing software teams.