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Google
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Field Solutions Architect, Generative AI, Google Cloud
Argentina
· Full-time
·
Not Applicable
Please submit your resume in English - we can only consider applications submitted in this language.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Santiago, Chile; Buenos Aires, Argentina.Minimum qualifications:
Responsibilities
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Santiago, Chile; Buenos Aires, Argentina.Minimum qualifications:
- 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.
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.
Key Skills
Ranked by relevance
ai
cloud
artificial intelligence
typescript
prototypes
embedded
python
react
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- Posted
- Feb 03, 2026
- Type
- Full-time
- Level
- Not Applicable
- Location
- Greater Buenos Aires
- Company
Industries
Information Services
Technology
Information
Internet
Categories
Project Management
Consulting
Engineering
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