As a GenAI Field Solutions Architect at Google Cloud, you will be an embedded builder to bridges the gap between frontier AI products and production-grade reality within customers. You will manage blocker to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity.
Requirements
- Bachelor’s degree in Engineering, Computer Science, a related field, or equivalent practical experience.
- 6 years of experience building and shipping production-grade AI-driven solutions to external or internal customers using Python, Typescript or comparable languages.
- Experience leading technical discovery sessions with business stakeholders and engineering teams to define AI and hardware infrastructure requirements.
- Experience architecting scalable AI systems on cloud platforms e.g., Google Cloud Platform (GCP).
- Experience building pipelines for structured, unstructured data, incorporating vector databases and retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.
Benefits
- Paid time off
- 401k matching
- Retirement plan
- Visa sponsorship
- Equity
- Bonus
