Join Google Cloud as an AI Outcome Customer Engineer and be instrumental in guiding enterprise clients through their digital transformation journey. This role focuses on bridging the gap between pre-sales technical evaluations and successful post-sales execution.

You will act as a key technical advisor, ensuring solutions are architected for rapid adoption and viable delivery. This involves deep dives into technical design, systemic debugging, and seamless integration of Google's cutting-edge AI and cloud technologies into customer IT ecosystems.

Google Cloud empowers organizations globally to innovate and solve critical business challenges. Become a vital part of a team that drives substantial business impact and helps companies achieve their most ambitious goals.

As an AI Outcome Customer Engineer, your primary responsibilities include:

Partnering with account teams to assess project feasibility and shape long-term adoption proposals. Leading the technical design for enterprise-grade AI solutions, ensuring secure and seamless integration into existing customer infrastructure. Diagnosing and resolving complex customer implementation issues by diving into code-level details and identifying core product bugs. Serving as the primary liaison to Product and Engineering teams, troubleshooting deployment blockers and translating field feedback into feature requests. Steering implementation strategy with technical authority and architectural foresight, owning the technical delivery process alongside customer-facing teams.

Ideal candidates will possess:

A Bachelor’s degree or equivalent practical experience is required.

Seven years of experience troubleshooting technical issues for internal/external partners or customers. Proven experience in leading technical delivery strategies, debugging complex systems, and collaborating with product and engineering organizations. Proficiency in reading or debugging code in a general-purpose language like Java, Python, or JavaScript. Experience with enterprise integrations, cloud infrastructure, or AI/ML model deployments. Familiarity with system design or orchestration frameworks.