Staff Software Engineer, AI Agent Architecture for Google Cloud Business Platforms
Sunnyvale, CA, USA · Staff · Full-time · Posted Oct 22, 2026
- Experience
- 8 years software development; 5 years testing and launching software products; 3 years software design and architecture; 5 years leading ML design and optimization; 2 years with GenAI techniques or related concepts. Preferred: 3 years technical leadership and 3 years in complex, matrixed cross-functional or cross-business projects.
- Education
- Bachelor's degree or equivalent practical experience.
About the job
Leads the architecture and development of an enterprise AI platform for building and operating AI applications, including agent workflows, enterprise knowledge models, and human-feedback learning loops.
What you'll do
- Design and implement the platform foundation, runtime, and interfaces for developing and orchestrating enterprise AI applications.
- Architect graph and ontology services for enterprise processes and multi-agent workflows; build integrations with Cloud and business systems.
- Set technical direction, lead design reviews, mentor engineers, and develop feedback loops that improve agent performance.
What they ask for
- Bachelor's degree or equivalent practical experience.
- 8 years of software development experience; 5 years testing and launching software products; 3 years in software design and architecture.
- 5 years leading ML design and optimizing end-to-end machine learning; 2 years with GenAI techniques or related concepts.
- Experience with AI Platforms/Gen AI Agents and Large-scale Distributed Systems.
Nice to have
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field; 3 years in technical leadership and setting technical direction.
- Experience with HITL workflows, feedback loops, automated evaluation, model distillation, or Google Cloud Platform technologies.
Pay
$207000 - $300000 (USD) base salary
Tools
GoogleSQL, Salesforce, SAP, Vertex AI, Gemini Enterprise, Google Cloud Platform
AI focus
Architects enterprise AI agents and workflows, ontology and graph models, generative interfaces, and human-feedback loops to improve agent accuracy.
Model-written summary · the original posting is authoritative