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Field Solutions Architect, Generative AI, Cloud
hace 5 horas
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 3 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 building pipelines for structured, unstructured data, incorporating vector databases and Retrieval-augmented generation (RAG)-like architectures to power enterprise-grade AI solutions.
- Experience architecting Artificial Intelligence (AI) systems on cloud platforms (GCP).
- Master's or PhD in AI, Computer Science, or a related technical field.
- Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google's ADK) and 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.
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 an "innovator-builder," 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 address blockers to production including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you serve a dual purpose: providing "white glove" deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud's future product roadmap. You will need to be able to travel 25% as required.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 a developer for complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable return on investment.
- Architect and code the "connective tissue" between Google's AI products and customer's live infrastructure, including Application Programming Interface (APIs), legacy data silos, and security perimeters as part of an expert team.
- Build high-performance evaluation (Eval) 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.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring long-term project success and high end-user adoption.
