Field Solutions Architect Manager, GenAI, Google Cloud
at Alphabet
Posted 5 hours ago
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- Compensation
- Not specified INR
- City
- Bengaluru, Mumbai
- Country
- India
Currency: INR
Lead a team of AI/ML engineers across India to translate AI products into production‑grade, customer‑facing solutions within Google Cloud. Provide technical mentorship while aligning with Product, Engineering, and Regional Sales to unblock production obstacles such as data readiness, integration, and state management. Own technical hiring for the Field Solutions Architect team, identify skill gaps in emerging AI technologies, and translate field insights into roadmaps and internal tools to drive efficiency. Focus on delivering enterprise‑grade agentic AI solutions and influencing customers, partners, and internal teams.
Field Solutions Architect Manager, GenAI, Google Cloud
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Minimum qualifications:
- Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 7 years of experience in cloud computing or a technical customer-facing role, with experience using Python.
- 2 years of experience managing a software engineering team, Field Solutions Architect team, or a similar technical customer-facing team in a cloud computing environment.
- Experience developing AI or Generative AI solutions utilizing AI Tools and designing multi-agent workflows and Retrieval-augmented generation (RAG) systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science, AI, Machine Learning, or a related technical field.
- Experience in designing interfaces for AI and agentic systems.
- Experience in architecting AI solutions within infrastructures, ensuring data sovereignty and secure governance.
- Ability to design observable multi-agent systems using design patterns (ReAct, self-reflection,etc), state management, and tool-calling protocols.
- Ability to perform ‘discovery' interviews to find the business problem and translate hardware/AI constraints for C-suites and technical teams.
About the job
The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.
As the Manager of the AI Field Solutions Architect (FSA) team, you will lead a team of AI/ML engineers across India who bridge the gap between AI products and production-grade reality within customers. You are responsible for a team that doesn't just consult, but codes, debug and deploys tailored agentic solutions directly within customer environments.
In this role, you will provide technical mentorship to your team while balancing alignment with Product, Engineering, and Google Cloud Regional Sales leadership. You will empower and unblock the team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management challenges that hinder AI from achieving enterprise-grade maturity.
Responsibilities
- Serve as the technical lead, establishing code standards, architectural standard procedures, and benchmarks to elevate engineering excellence across the team.
- Partner with Sales and Tech Leadership to define requirements for opportunities, deploying experts (MLOps, GenMedia, or Agentic systems) to key accounts.
- Lead technical hiring for the Field Solutions Architect team, evaluating AI/ML expertise, systems engineering, and coding skills to build the engineering squad.
- Identify skill gaps in emerging tech (tool-calling, and foundation models), ensuring the team maintains subject-matter-expertise in an evolving AI stack.
- Collaborate with Product and Engineering to resolve blockers and translate field insights into road maps while building internal tools to drive organizational efficiency.
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