Minimum qualifications :

- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience
- 6 years of experience shipping production-grade AI-driven solutions to external or internal customers.
- Experience architecting scalable AI systems on cloud platforms (e.g., Google Cloud Platform).

Preferred qualifications :

- Master’s degree 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 complex patterns like ReAct, self-reflection, and hierarchical delegation.
- Experience developing GenAI solutions utilizing foundation models, 1P model tuning, and advanced RAG architectures.
- Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing.
- Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication.

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.

In this role, you will handle 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,



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 :

- Architect and code the connective tissue 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 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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment chance regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

📌 Field Solutions Architect, Generative Ai, Google Cloud (Mumbai)
🏢 Google
📍 Mumbai