AI Outcome Engineer, Forward Deployed Engineering
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 3 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).
Preferred qualifications:
- Experience interfacing directly with core product/engineering organizations regarding infrastructure or AI/ML model deployments, managing technical delivery strategies, and debugging systems.
About the job
As an AI Outcome Customer Engineer (OCE) you will embed with our customers to drive the adoption of Google Cloud enterprise AI products, acting as a trusted advisor to customer stakeholders, partners, and internal product and engineering teams. You will develop, manage and execute the AI deployment plan, by providing technical leadership, applying your skills in Enterprise Architecture, consultative delivery, Applied Artificial Intelligence engineering, and AI solution engineering. You will have a direct impact on the velocity of customer adoption and business outcomes realised through the successful deployment of enterprise AI solutions and use cases.
You will blend delivery expertise, market and industry knowledge, technical implementation, and technical project leadership to realise the value of Google Cloud AI with our customers.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Spain: €70000 - €71500 (EUR) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- 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.
- Identify and develop opportunities for new enterprise AI use cases during project execution.
- Drive sustainable product usage to help customers realize ongoing business value.
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