Senior Staff Tech Lead, Google Retail Ads
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Sep 23, 2026. Google scores B on the Alion truth index.
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.
We work on the retail segment of Search Ads, driving advertiser goals through performance, directives, and insights to empower businesses in the retail ecosystem.
In this role, you'll shape how retailers connect with customers in the age of AI. You will define the technical and strategic roadmap for signals, LTV value, optimization, and advertiser directives. By leading cross-functional teams, you will build the foundational intelligence that powers automated value delivery across Search Ads for Retail. You will require a strong understanding of auction dynamics, prediction and quality systems, and advertiser-facing tools.
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: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Own the technical and strategic roadmap for retail signals, goals and optimization. As we enter the age of AI transformation on search, we have a need to improve the user understanding, advertiser intent and LTV value definition to power automated value delivery for retailers.
- Lead the solution space, that is distributed across multiple teams, technically and strategically, while working with PM.
- Work with PMs and Executives, identify the right areas of improvements, making sure all the areas come together (e.g., how we consolidate different tools for value adjustments and use consistently across predictions and optimization).
- Work with senior cross-product area partners to leverage their expertise and infrastructure.
Qualifications
Minimum qualifications:
Bachelor's degree or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages, and with data structures and algorithms.
- 8 years of experience testing, maintaining or launching software products, and 5 years of experience with software design and architecture.
- Experience in Ads or Search products.
Preferred qualifications:
- Track record of leading multi-disciplinary projects from conception to execution, with the ability to influence and align stakeholders across Engineering, Product, and Sales.
- Familiarity with how AI-driven signals and ML models translate into retail-specific business value and user-facing improvements.
- Understanding of performance optimization within a constrained environment, including the ability to balance trade-offs between automated value delivery and system limitations.
- Ability to synthesize complex datasets and various performance metrics into actionable strategic insights and clear technical roadmaps.
- Ability to navigate ambiguity and "connect the dots" across various product areas to build a long-term goal for retail advertising.