Field Solutions Architect GenAI Google Cloud
Job Overview
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Job Description
About the Role
The Field Solutions Architect GenAI Google Cloud position is responsible for bridging the gap between frontier AI products and production-grade systems. In this role, you will code, debug, and deploy bespoke agentic solutions directly in the customer environment, ensuring seamless integration with enterprise systems.
Key Responsibilities
- Lead development of AI applications from prototype to production.
- Architect and code integrations between Google AI products and customer infrastructure.
- Build high-performance evaluation pipelines and observability frameworks.
- Identify field friction points and convert insights into reusable modules.
Qualifications
Minimum Qualifications: Bachelor's degree in Science, Technology, Engineering, or Mathematics with 8 years of experience implementing production-grade AI solutions in Python and architecting AI systems on cloud platforms. Experience in leading technical discovery with C-suite and engineering teams and building full-stack solutions.
Preferred Qualifications: Advanced degree in Computer Science, AI or related field, experience scaling enterprise-grade ML systems, resilient data pipelines with BigQuery and Vertex AI, and proficiency in CI/CD using Vertex AI Pipelines, Kubeflow, or MLflow.
About Google Cloud
Google Cloud Platform helps customers transform their business using secure, reliable and scalable cloud technology. As a Field Solutions Architect, you will play a key role in directly impacting customer success and the evolution of Google's AI product roadmap.
Key skills/competency
- AI
- Cloud
- Python
- ML systems
- Enterprise integration
- BigQuery
- Vertex AI
- CI/CD
- Data engineering
- Technical leadership
How to Get Hired at Google
- Research Google: Study their culture, products, and leadership.
- Customize your resume: Emphasize full-stack AI and cloud projects.
- Showcase technical expertise: Highlight Python and AI solution experience.
- Prepare for interviews: Practice technical discovery and problem-solving questions.
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