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AI Outcome Customer Engineer, FDE, Google Cloud
GoogleMountain View, CA, USA10+ years
Apply Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mumbai, Maharashtra, India; Bengaluru, Karnataka, India.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 10 years of experience troubleshooting technical issues for internal/external partners or customers.
- Experience leading technical delivery strategies, debugging systems, and interfacing with product/engineering organizations.
- Experience with enterprise integrations (APIs, enterprise content management (ECMs), identity), Cloud infrastructure, or AI/ML model deployments.
- Experience reading or debugging code in a general purpose coding language (e.g., Java, Python, JavaScript, etc.).
- Experience in system design or orchestration frameworks.
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
The Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate.
As an AI Outcome Customer Engineer, Forward Deployed Engineering (FDE) you will embed with strategic 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 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 realized 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 realize the value of Google Cloud AI with strategic customers.
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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