Field Solutions Architect, Generative AI, Google Cloud
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At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sydney NSW, Australia; Melbourne VIC, Australia.Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience
- 8 years of experience shipping production-grade AI-driven solutions to external or internal customers in Python.
- Experience architecting AI systems on cloud platforms.
- Experience developing GenAI solutions utilizing foundation models, 1P model tuning, and RAG architectures.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and complex patterns like ReAct, self-reflection, and hierarchical delegation.
- Knowledge of 'LLM-native' metrics (tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
- Proven ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.
- Proven ability to build full-stack applications that interact with complex enterprise IT infrastructures.
- Ability to perform deep discovery interviews and translate complex hardware/AI constraints for C-suites and deep-technical teams.
About the job
As a Field Solutions Architect at Google Cloud, you are an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you function as a 'builder-consultant', moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.
This role is designed for high-agency engineers with a founder’s mindset. You will work on blocker to production including solving the integration complexities, data readiness issues, and state-management challenges that prevent AI from reaching enterprise-grade maturity. By embedding with strategic accounts, you serve a dual purpose: providing 'white glove' deployment of complex AI systems and acting as a critical feedback loop, and transforming real-world field insights into Google Cloud’s future product roadmap.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Serve as the lead developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code the connection between Google’s AI products and customer's live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous requirements for accuracy, safety, and latency.
- Identify repeatable field patterns and technical 'friction points' in Google’s AI stack, converting them into reusable modules or formal product feature requests for the engineering teams.
- Drive engineering excellence across the JAPAC region by mentoring talent, co-building with customer teams to instill best practices, and influencing cross-functional strategies to uplevel organizational technical capabilities.
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