Senior Staff Software Engineer, AI Mode and AI Overviews Helpfulness

Google•New York, NY

3d•$262,000 - $364,000

About The Position

Google is seeking a Senior Staff Software Engineer to improve the quality of its AI Overviews and AI Mode experiences in Google Search. The team works with DeepMind partners to improve underlying models and end-to-end quality through prompt optimization, quality evaluations, and live experiments. Its mission is to make responses helpful by including the right content in an easy-to-consume way. The role focuses on making Google Search’s flagship generative AI experiences a trusted knowledge companion, with natural and effortless conversations. The engineer will help address complex engineering challenges and expand Search infrastructure while maintaining an accessible and useful experience for people around the world. Google software engineers work on important projects and are expected to show leadership, versatility, and enthusiasm for solving problems across the full stack.

Requirements

Bachelor’s degree or equivalent practical experience.
8 years of experience in software development.
7 years of experience leading technical project strategy and ML design, and working with end-to-end applied machine learning, such as model deployment, model evaluation, data processing, and debugging.
5 years of experience with design and architecture, and testing and launching software products.
Experience in AI/ML quality evaluation and improvement.
Experience integrating generative AI tools or LLM interfaces into workflows.

Nice To Haves

Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
8 years of experience with data structures and algorithms.
5 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.
Experience driving quality improvements out-of-model (prompting, APO, modular serving, orchestration) and in-model (post-training and evaluations).

Responsibilities

Own the technical strategy and roadmap for whole-response helpfulness across AI Mode and AI Overviews.
Architect scalable quality infrastructure and closed-loop self-improving systems that shorten the path from experiment to launch.
Drive quality improvements out-of-model and in-model.
Define how measurement, hill-climbing, and upstreaming should be adjusted to account for response aspects beyond text.
Establish strong collaborations to align priorities and technical direction.