Field Solutions Architect, Google Cloud, Applied AI

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 will take initial conversational prototypes and transform them into production-ready solutions, owning the engineering life-cycle and the transition from the "Art of the Possible" to real-world business value and scalable, secure AI systems. Focused on leading technical delivery for Conversational AI pilots, you will establish the first Customer User Journeys (CUJs) for our largest customers at their sites, utilizing your understanding of software engineering, 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.

Locations
:
New York, NY, USA;
Atlanta, GA, USA;
Playa Vista, CA campus may also be available. Applications window remains open until at least February 04, 2026, and this opportunity will remain online based on business needs.

Applicants in various jurisdictions are considered under local fair chance ordinances and laws where applicable. In accordance with Washington state law, we highlight our comprehensive benefits package, available to all eligible US-based employees.

• Health, dental, vision, life, disability insurance
• Retirement Benefits: 401(k) with company match
• Paid Time Off: 20 days per year, accrual 6.15 hours per pay period for the first five years
• 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 year

Note
:
By applying to this position you will have an opportunity to share your preferred working location from the following:
New York, NY;
Atlanta, GA;
Austin, TX;
Boulder, CO;
Chicago, IL;
Addison, TX;
Kirkland, WA;
Miami, FL;
Mountain View, CA;
Los Angeles, CA;
Reston, VA;
Seattle, WA;
San Francisco, CA;
Washington, D.C.

• Serve as the lead developer for Conversational AI and Customer Experience (CX) applications, transitioning from rapid prototypes to production-grade agentic workflows that drive measurable ROI.
• Architect conversational flows optimized for connectivity between Google’s Conversational AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters.
• Build high-performance evaluation (Eval) pipelines and observability frameworks to optimize 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 AI 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 long-term project success and high end-user adoption.

• Bachelor’s degree in Computer Science or equivalent practical experience in Software Engineering, SRE, or Dev Ops.
• 3 years of experience in Python, and experience architecting scalable AI systems on cloud platforms.
• Experience deploying conversational agents using code-based frameworks.
• Experience deploying resources via Terraform or similar tools, and automating the setup of agents, functions, and networking.
• Experience building full-stack applications that interact with enterprise IT infrastructures.

• Master’s degree or PhD in AI, Computer Science, or a related technical field.
• Experience implementing multi-agent systems using frameworks like ReAct and self-reflection.
• Experience debugging Agent logic and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
• Experience connecting agents to…