Staff Software Engineer, Ads and Commerce Advisor Platform
Mountain View, CA, USA · Staff · Full-time · Posted Oct 7, 2026
- Experience
- 8 years in software development; 5 years testing and launching software products; 3 years in software design and architecture; 5 years leading ML design and optimizing ML infrastructure; 2 years with GenAI techniques or related concepts. Preferred: 8 years with data structures and algorithms; 3 years in technical leadership; 3 years in a complex, matrixed organization.
- Education
- Bachelor's degree or equivalent practical experience; preferred: Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
About the job
Sets technical direction and builds Google Ads and Commerce’s full-stack agentic runtime for conversational and proactive AI experiences.
What you'll do
- Own the orchestration runtime roadmap, including reasoning, tool calling, memory, agent protocols, and streamed responses.
- Guide adoption of new models and inference APIs, and plan migrations while preventing regressions.
- Mentor engineers, establish design and code review standards, and improve discovery, versioning, and governance of platform skills and tools.
What they ask for
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development; 5 years testing and launching software products; and 3 years in software design and architecture.
- 5 years leading ML design and optimizing ML infrastructure.
- 2 years with state-of-the-art GenAI techniques or GenAI-related concepts.
Nice to have
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years with data structures and algorithms; 3 years in technical leadership; and 3 years in a complex, matrixed organization involving cross-functional or cross-business projects.
Pay
$207000 - $300000 USD base salary
Tools
Gemini, LLMs, Multi-Modal, Large Vision Models
AI focus
Builds and operates an agentic runtime for conversational and proactive AI, including orchestration, model and inference API adoption, prompting, tool calling, memory, and ML infrastructure.
Model-written summary · the original posting is authoritative