Cloud Field Solutions Architect, Applied AI, Google Cloud
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This role may also be located in our Playa Vista, CA campus.
"Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act."
Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per yearNote: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Atlanta, GA, USA; Austin, TX, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Kirkland, WA, USA; Miami, FL, USA; Mountain View, CA, USA; Los Angeles, CA, USA; Reston, VA, USA; Seattle, WA, USA; San Francisco, CA, USA.
Minimum qualifications:
- Bachelor’s degree in Computer Science or equivalent practical experience.
- 3 years of experience in Python and architecting AI systems on cloud platforms.
- 3 years of experience developing full-stack applications integrated with enterprise IT infrastructures (e.g., ERP, CRM, or legacy databases) and managing technical projects.
- 2 years of experience developing conversational agents using code-based frameworks (e.g., LangChain, Dialogflow CX, or Rasa) and deploying generative AI tools.
- Experience in deploying resources via Terraform or similar tools to automate the setup of agents, functions, and networking.
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 patterns like ReAct, self-reflection, and hierarchical delegation.
- Experience debugging Agent logic and enhancing tool selection, including tracing conversation IDs across micro-services to identify and resolve failures.
- Experience connecting agents to enterprise knowledge bases and enhancing Retrieval-Augmented Generation chunking.
- Experience in troubleshooting live, high-traffic systems during critical operations.
- Ability to travel up to 50% of the time as needed.
About the job
As a Field Solutions Architect (FSA) in Applied AI, you are the "Agent Engineer" and the primary delivery arm for our customers' most critical AI initiatives. You take initial conversational prototypes and transform them into production-ready solutions, owning the engineering life cycle, including the transition from "Art of the Possible" to real-world business value, secure AI systems. This is a high-travel, high-impact role focused on leading technical delivery for Conversational AI pilots and establishing the first Customer User Journeys (CUJs) for our largest customers at their sites. This role requires an understanding of software engineering, stands for Machine Learning Operations (MLOps), and cloud infrastructure.
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.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Serve as the lead developer for Conversational AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive return on investment.
- Architect and code conversational flows that are not just functional, but enhanced for the "connective tissue" between Google’s Conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
- Build Evaluation pipelines and observability frameworks to enhance agentic workloads, focusing on reasoning loops, tool selection, and reducing latency while maintaining production-grade security and networking.
- Identify repeatable field patterns and technical "friction points" in Google’s Applied Artificial Intelligence (AAI) stack, converting them into reusable modules or product feature requests for Engineering teams.
- Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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