The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.
As a Practice Customer Engineer (CE) with a specialty in AI, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will leverage your expertise in our strategic product areas in partnership with Platform CEs, writing code, developing prototypes, proofs-of-concept, and demos to promote new specialized solutions to customers. You will solve AI-centered customer issues and provide a critical feedback loop to influence product development. You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales skills, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio.
Leading with the future, the AI GTM team are trusted AI advisors, scaling across Google to deliver transformative customer experiences that shape the next generation of their business.
It's an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll excel by leveraging Google's brand credibility—a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world's most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind's engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era—the market is yours.
Responsibilities
- Drive the technical solution for workloads within AI product areas to ensure successful adoption, primarily supporting the business-cycle from technical evaluation through customer ramp.
- Combine sales strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
- Provide deep technical consultation to customers, acting as a technical advisor and building lasting customer relationships.Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.
- Leverage learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
- Work within Product and Engineering management systems to document, prioritize and drive resolution of customer feature requests and issues.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience with Banking or Financial services.
- Experience engaging with, and presenting to, technical stakeholders and executive leaders.
Preferred qualifications:
- Experience in developing agents using frameworks such as LangGraph, Semantic Kernel, or the Google AI Agent Development Kit (ADK).
- Experience with cloud technologies including SaaS applications, iPaaS, business automation solutions, Cloud infrastructure, Agentic AI, and cloud networking.
- Knowledge of integration patterns using OpenAPI and Model Context Protocol (MCP) to connect AI agents with business systems and Application Programming Interface (API) Gateways.
- Knowledge of observability constructs including distributed tracing, logging, and audit logging for AI applications.