> Markdown version of [/jobs/ext/2979133-ai-outcome-customer-engineer-forward-deployed-engineering-google-cloud](https://www.wearedevelopers.com/jobs/ext/2979133-ai-outcome-customer-engineer-forward-deployed-engineering-google-cloud). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Outcome Customer Engineer, Forward Deployed Engineering, Google Cloud - **Company:** Google - **Location:** Madrid, Spain - **Salary:** €120,000.0 - €123,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, C++ (Programming Language), Cloud Computing, Software Debugging, Enterprise Content Management, Python (Programming Language), Machine Learning, Google Cloud - **Published:** September 18, 2026 - **Apply:** https://dejobs.org/x/x/081BE733AAF8406EAC964D5597F0A020/job/ ## About the Role Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain. Share AI Outcome Customer Engineer, Forward Deployed Engineering, Google Cloud, * Bachelor's degree or equivalent practical experience. * 7 years of experience troubleshooting technical issues for internal/external partners or customers. * Experience in either system design or reading code (e.g., Java, C++, Python). * Experience with Interfaces (APIs), Enterprise Content Management (ECMs), identity, cloud infrastructure, or AI/ML model deployments., * Experience leading technical delivery strategies, debugging systems, and interfacing directly with core product/engineering organizations. ## Description * Develop and orchestrate a structured, end-to-end deployment plan across customer, professional services, and partner teams, onboarding the implementation team, clearing blockers, managing timelines and progress, and ensuring readiness. * Employ code development, debugging, or systems design to resolve technical blockers and accelerate customer time-to-value. * Drive and track progress of the initial and ongoing adoption of enterprise AI, accelerating customers from initial agreement to business outcomes as quickly as possible. * Drive sustainable product usage to help customers realize ongoing business value.