Minimum qualifications :

- Bachelor’s degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience.
- 8 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms.
- Experience leading technical discovery sessions with executive stakeholders (C-suite) and engineering teams to define AI and hardware infrastructure requirements.
- Experience building full-stack solutions that interface with enterprise systems.

Preferred qualifications :

- Master's degree or PhD in Computer Science, AI, Machine Learning, or a related technical field.
- Experience in implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation.
- Knowledge of Large Language Model (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 Model Context Protocol (MCP), tool-calling, and Open Authorization (OAuth)-based authentication.

About the job : As a Field Solutions Architect at Google Cloud, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production grade reality within customers. Unlike traditional advisory roles, you will function as a 'builder-consultant', moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s workplace. You will address blockers to production, including solving the integration complexities, data readiness, and state management issues that prevent Artificial Intelligence (AI)



from reaching enterprise grade maturity. You will serve a dual purpose: providing 'white glove' deployment of Artificial Intelligence (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 Artificial Intelligence (AI) products and customer's live infrastructure, including Application Programming Interfaces (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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity 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, Genai, Google Cloud (Gurugram)
🏢 Google
📍 Gurugram