Customer Engineer, Cloud AI

About the Role

As a Customer Engineer specializing in Cloud AI at Google, you will be a key technical expert partnering with sales teams to drive the adoption and success of Google Cloud solutions. Your role involves accelerating technical wins for complex, specialized workloads by leveraging deep expertise in strategic product areas. You will be directly involved in writing code, developing prototypes, proofs-of-concept, and demos to showcase new, highly specialized AI solutions to customers. Furthermore, you will play a crucial part in solving AI-centered customer issues and providing critical feedback to influence product development. This position requires excellent organizational, communication, and presentation skills to effectively engage with customers, understand their business and technical requirements, and present practical, valuable solutions on Google Cloud. You will combine sales acumen, market knowledge, and direct technical engagement to demonstrate the value of the Google Cloud portfolio.

Google Cloud empowers organizations to digitally transform their businesses and industries with enterprise-grade solutions built on Google’s cutting-edge technology and sustainable developer tools. Customers across more than 200 countries and territories rely on Google Cloud as a trusted partner to foster growth and resolve their most critical business challenges.

Minimum Qualifications

• Bachelor’s degree or equivalent practical experience.
• 4 years of experience with cloud native architecture in an industry, customer-facing, or support role.
• Experience engaging with, and presenting to, technical stakeholders and executive leaders.
• Experience with machine learning model development and deployment.
• Experience using programming languages (e.g., Python, JavaScript/TypeScript) to demo, prototype, or workshop with customers.
• Experience with AI agent orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen), agentic design patterns (e.g., tool-use, multi-agent collaboration), and integrating large language models into autonomous workflows using advanced API prompting and Retrieval-Augmented Generation (RAG).

Preferred Qualifications

• Master's degree in Computer Science, Engineering, Mathematics, a technical field, or equivalent practical experience.
• Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks).
• Experience in architecting and developing software or infrastructure for scalable, distributed systems.
• Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), or using machine learning APIs.
• Ability to learn quickly, understand, and work with new emerging technologies, methodologies, and solutions in the cloud/IT technology space.

Responsibilities

• Drive the technical win for complex workloads within Cloud AI, ensuring successful adoption from technical evaluation through customer ramp-up.
• Combine sales strategies with direct development and prototyping to deliver functional, customer-tailored solutions that secure buy-in from domain experts.
• Provide deep technical consultation to customers, serving as a trusted technical advisor and building strong, lasting customer relationships.
• Leverage insights from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
• Collaborate with Product and Engineering management systems to document, prioritize, and facilitate the resolution of customer feature requests and issues.

Key Skills/Competency

• Cloud AI
• Machine Learning
• Solution Architecture
• Technical Sales
• Prototyping
• Python
• LLM Integration
• RAG
• Customer Engagement
• Google Cloud Platform (GCP)