Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products.
- 5 years of experience with full stack development, across back-end such as Java, Python, Golang, or C++ codebases, and front-end experience including JavaScript or TypeScript, HTML, CSS or equivalent.
- 3 years of experience with software design and architecture.
- Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
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.
As a part of the Display and Video 360 (DV360), Google's cross-exchange real-time bidding buying platform, you will help remake the way advertising is done on the internet, making it more targeted and more valuable. You will give customers access to 100 billion ad impressions per day as it is one of the fastest growing products at Google.
As a part of the DV360 Inventory and Deals Team, you will be responsible for building intelligent features that support enterprise customers (agencies and large advertisers) to efficiently discover inventory, negotiate deals, execute campaigns and maximize performance across the real-time bidding ads ecosystem.
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.
Responsibilities:
- Manage and mentor a sub-team within the DV360 Inventory and Deals organization, fostering technical excellence, leadership, and strong engineering velocity.
- Lead the end-to-end system architecture and implementation of user-facing products and partner-facing APIs across Java, Spanner, and Angular/Dart.
- Guide technical strategy across our AI-powered natural language discovery roadmap, collaborate directly with engineers at external exchanges on API specifications, and ensure our 24/7 infrastructure scales reliably.
- Balance people leadership with technical contribution, spending approximately half of the time designing, coding, and landing critical features.
- Drive architectural modernization across our data and serving layers, deprecating legacy synchronous dependencies in favor of event-driven, push-down query architectures.