Senior GenAI & Search Intelligence Architect

Google; Mountain View (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google is seeking a senior software engineer to join the User-AI Flywheel within Search Intelligence. You will lead design and implementation of large-scale ML systems, contribute to model deployment, evaluation, and data processing, and collaborate across teams to ship impactful AI features.

The role emphasizes leadership, innovation, and the ability to tackle complex problems across the full stack, including safety, reliability, and performance at scale in a global product environment.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and optimizing industry-scale ML infrastructure.
• 5 years of experience with design and architecture; and testing/launching software products.
• 2 years of experience with GenAI techniques or related concepts.

Responsibilities

• Advocate the development of modeling, tuning, and optimization techniques to support LLM performance.
• Guide the design and implementation of user-signal-driven improvements of LLMs.
• Partner with Google Research and DeepMind to advance LLM technologies.
• Demonstrate exceptional teamwork and coding practices in the LLM domain.
• Cultivate relationships with stakeholders to define and execute LLM initiatives.

Skills

ML design

Model deployment

Data processing

Debugging

Fine tuning

System design

LLMs

Technical leadership

Education

Bachelor's degree or equivalent practical experience

Master’s degree or PhD in Engineering, Computer Science, or related field

Job description

Google is seeking a senior software engineer to join the User-AI Flywheel within Search Intelligence. You will lead design and implementation of large-scale ML systems, contribute to model deployment, evaluation, and data processing, and collaborate across teams to ship impactful AI features.

The role emphasizes leadership, innovation, and the ability to tackle complex problems across the full stack, including safety, reliability, and performance at scale in a global product environment.