Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 7 years of experience troubleshooting technical issues for internal/external partners or customers.
- Experience leading technical delivery strategies, debugging systems, and collaborating with product/engineering organizations.
- Experience with enterprise integrations (e.g., APIs, enterprise content management (ECMs), identity), cloud infrastructure, or AI/ML model deployments.
- Experience in system design or orchestration frameworks.
- Ability to communicate in English and Japanese fluently to support client relationship management in this region.
Preferred qualifications:
- Experience orchestrating specialized technical resources to execute complex builds.
- Experience engaging with, presenting to, and influencing technical stakeholders or executive leaders.
- Ability to dive deep into novel technical problems, decipher extreme ambiguity, diagnose bugs, and emerge with credible architectural solutions.
- Excellent executive communication skills, capable of translating deep technical integration issues into business impact.
About the job
As an AI Outcome Customer Engineer, Forward Deployed Engineering, you will be responsible as an enterprise architect, technical debugger, and engineering liaison. You will bridge the gap between pre-sales agreement shaping and post-sales execution. Entering the agreement cycle during the technical evaluation phase for strategic accounts, you will ensure that solutions are shaped strictly through the lens of adoption, rapid activation, and viable delivery.
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
- Partner with Account teams and practice Customer Engineer (CEs) during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDE engagement requests.
- Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries.
- Dive into code-level context to diagnose and resolve complex customer implementation issues, identify core product bugs, and test workarounds to clear execution roadblocks.
- Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests.
- Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams.
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