Customer Engineer, Cloud AI, Cloud

About This Role

This Customer Engineer role specializes in Cloud AI within Google Cloud, partnering with technical sales teams to showcase Google Cloud's capabilities to customers. The role involves acting as a technical expert to drive the adoption of complex, specialized AI workloads, developing prototypes, proofs-of-concept, and demos for new solutions. You will solve AI-centered customer challenges and provide feedback to influence product development.

Responsibilities

• Partner with technical sales teams to differentiate Google Cloud to customers
• Serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads
• Leverage deep expertise in strategic product areas, in partnership with Platform CEs, to write code and develop prototypes, proofs-of-concept, and demos
• Sell new, highly specialized solutions to customers
• Solve AI-centered customer challenges
• Provide a critical feedback loop to influence product development
• Engage with customers to understand their business and technical requirements
• Persuasively present practical and useful solutions on Google Cloud
• Blend sales prowess, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio

Requirements

• Bachelor's degree or equivalent practical experience
• 10 years of experience with cloud native architecture in a customer-facing or support role
• Experience with Machine Learning model development and deployment
• Experience with AI agent orchestration frameworks (e.g., Lang Graph, CrewAI, Auto Gen), agentic design patterns (e.g., tool-use, multi-agent collaboration), or integrating models into autonomous workflows via advanced API prompting or RAG
• Experience working with, or presenting to, technical stakeholders or executive leaders

Nice to have:

• 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 architecting and developing software or infrastructure for scalable, distributed systems
• Experience learning and working with new emerging technologies, methodologies, and solutions in the cloud/IT technology space
• Experience with deep learning frameworks (e.g., PyTorch, Tensor Flow, Jax, Ray), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), or using machine learning APIs

Benefits

• 42.86% bonus target
• Equity
• Benefits