Customer Engineer, Cloud AI, Google Cloud

• Drive the technical win for complex workloads within Cloud AI to ensure rapid and successful adoption, primarily supporting the sales 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.
• 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.

Minimum qualifications:

• 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 or deployment.
• Experience with AI agent orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen), agentic design patterns (e.g., tool-use, multi-agent collaboration), or integrating models into autonomous workflows via advanced API prompting or RAG.
• Experience engaging with, and presenting to, technical stakeholders and executive leaders.

Preferred qualifications:

• Master's degree in Computer Science, Engineering, Mathematics, or a technical field.
• Experience 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, TensorFlow, Jax, Ray), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers), or using machine learning APIs.

• 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 or deployment.
• Experience with AI agent orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen), agentic design patterns (e.g., tool-use, multi-agent collaboration), or integrating models into autonomous workflows via advanced API prompting or RAG.
• Experience engaging with, and presenting to, technical stakeholders and executive leaders.