AI Solution Architect Jobs at Google with Visa Sponsorship
AI Solution Architect roles at Google sit at the intersection of applied AI and enterprise client strategy, requiring deep technical fluency and the ability to translate complex solutions into business outcomes. Google has a strong track record of sponsoring work visas for this function across H-1B, H-1B1, and E-3 categories.
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Get Access To All JobsINTRODUCTION
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.
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. This role may also be located in our Playa Vista, CA campus.
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 year
The application window will be open until at least April 15, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Kirkland, WA, USA; Miami, FL, 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 in Software Engineering, Site Reliability Engineering (SRE), or DevOps.
- 6 years of experience in Python and experience architecting scalable AI systems on cloud platforms.
- Experience deploying conversational agents using code-based frameworks and build in real-time with customers utilizing modern generative AI tools.
- Experience in deploying resources via Terraform or similar tools to automate the setup of agents, functions, and networking.
- Experience building full-stack applications (not just scripts) that interact with enterprise IT infrastructures also in developing and driving customer projects forward in a timely manner.
PREFERRED QUALIFICATIONS
- Master’s degree 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 debugging Agent logic (ReAct loops, Chain of Thought) and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
- Proven track record of troubleshooting live, high-traffic systems during critical windows.
- Ability to travel up to 50% of the time.
ABOUT THE JOB
As a Forward Deployed Engineer (FDE) 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 end-to-end engineering life-cycle, including the transition from "Art of the Possible" to real-world business value and scalable, 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 a deep 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.
The US base salary range for this full-time position is $153,000-$222,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
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 complex Conversational AI and CX applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" 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 complex 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 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 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 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.
INTRODUCTION
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.
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. This role may also be located in our Playa Vista, CA campus.
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 year
The application window will be open until at least April 15, 2026. This opportunity will remain online based on business needs which may be before or after the specified date.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Boulder, CO, USA; Chicago, IL, USA; Addison, TX, USA; Kirkland, WA, USA; Miami, FL, 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 in Software Engineering, Site Reliability Engineering (SRE), or DevOps.
- 6 years of experience in Python and experience architecting scalable AI systems on cloud platforms.
- Experience deploying conversational agents using code-based frameworks and build in real-time with customers utilizing modern generative AI tools.
- Experience in deploying resources via Terraform or similar tools to automate the setup of agents, functions, and networking.
- Experience building full-stack applications (not just scripts) that interact with enterprise IT infrastructures also in developing and driving customer projects forward in a timely manner.
PREFERRED QUALIFICATIONS
- Master’s degree 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 debugging Agent logic (ReAct loops, Chain of Thought) and optimizing tool selection, including tracing conversation IDs across microservices to identify and resolve failures in real-time.
- Experience connecting agents to enterprise knowledge bases and optimizing RAG chunking to prevent hallucinations.
- Proven track record of troubleshooting live, high-traffic systems during critical windows.
- Ability to travel up to 50% of the time.
ABOUT THE JOB
As a Forward Deployed Engineer (FDE) 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 end-to-end engineering life-cycle, including the transition from "Art of the Possible" to real-world business value and scalable, 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 a deep 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.
The US base salary range for this full-time position is $153,000-$222,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
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 complex Conversational AI and CX applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive measurable ROI.
- Architect and code conversational flows that are not just functional, but optimized for the "connective tissue" 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 complex 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 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 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 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.
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Get Access To All JobsTips for Finding AI Solution Architect Jobs at Google Jobs
Frame your credentials around production AI systems
Google's AI Solution Architect hiring emphasizes hands-on deployment experience, not just theoretical knowledge. Before applying, document specific systems you've architected using tools like TensorFlow, Vertex AI, or equivalent platforms, with clear outcomes tied to business value.
Target Google Cloud's enterprise and strategic accounts teams
AI Solution Architect openings at Google cluster within Google Cloud's customer-facing divisions. Searching for roles tied to enterprise accounts or industry verticals like financial services and healthcare surfaces the most active hiring pipelines for this function.
Distinguish yourself during the technical system design interview
Google's interview loop for this role includes a system design round focused on scalable AI architectures. Prepare to walk through end-to-end ML pipeline design, including data ingestion, model serving, and monitoring, using Google Cloud-native components where possible.
Confirm your visa category eligibility before accepting an offer
Google sponsors H-1B, H-1B1, and E-3 visas for this role. Australian citizens should confirm E-3 eligibility with the recruiter early, since E-3 petitions can be filed year-round without lottery exposure and with faster processing than standard H-1B filings.
Use Migrate Mate to surface active AI Solution Architect openings at Google
Sponsorship-confirmed roles at large employers fill quickly and aren't always easy to identify across standard job boards. Use Migrate Mate to filter AI Solution Architect positions at Google that are open to visa sponsorship, so you're applying to the right openings from the start.
Understand how Google handles H-1B cap timing for new hires
If you're not currently in H-1B status, Google must file during the annual USCIS cap season with an October 1 start date. Factor the April lottery window and a potential six-month wait into your negotiation timeline when discussing a start date with your recruiter.
AI Solution Architect at Google jobs are hiring across the US. Find yours.
Find AI Solution Architect at Google JobsFrequently Asked Questions
Does Google sponsor H-1B visas for AI Solution Architects?
Yes, Google sponsors H-1B visas for AI Solution Architect roles. The company is a registered H-1B employer and has a consistent track record of filing petitions for technical and client-facing roles in this category. If you're subject to the H-1B cap, Google's recruiting team will guide you through the April registration window and the October 1 start date process.
How do I apply for AI Solution Architect jobs at Google?
Applications go through Google's careers portal at careers.google.com. Search for AI Solution Architect roles under Google Cloud. The process typically includes an initial recruiter screen, a technical phone interview covering AI and ML fundamentals, a system design round, and a behavioral interview loop. Indicate your visa sponsorship needs early so the recruiting team can align timelines accordingly. Migrate Mate also lists active Google openings filtered by sponsorship eligibility.
Which visa types does Google commonly use for AI Solution Architect roles?
Google files H-1B petitions for the broadest pool of international candidates. Australian citizens can request E-3 sponsorship, which bypasses the lottery and allows year-round filing. Candidates from Chile or Singapore may qualify for the H-1B1. All three categories require Google to file a certified Labor Condition Application with the DOL before the petition is submitted to USCIS.
What qualifications does Google expect for AI Solution Architect candidates?
Google typically looks for a bachelor's degree or higher in computer science, electrical engineering, or a closely related field, combined with direct experience designing and deploying production AI or ML systems. Familiarity with Google Cloud products, particularly Vertex AI and BigQuery, is a strong advantage. Client-facing experience, the ability to present technical architectures to non-technical stakeholders, and prior work in enterprise or strategic accounts settings also carry significant weight in the evaluation process.
How long does the visa sponsorship process take once Google extends an offer?
Timeline depends on your visa category. E-3 and H-1B1 filings can be adjudicated within a few weeks if filed at a consulate outside the U.S. Cap-subject H-1B petitions require registration in April and cannot start until October 1, meaning a five-to-six month gap between offer and start date is common. USCIS premium processing, which Google has historically made available for sponsored hires, can reduce adjudication to roughly 15 business days once the petition is filed.
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