Customer Engineer, Cloud AI, Google Cloud

About Google A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone. Check out our career opportunities at goo.gle/3DLEokh

Google

searchadsmobileandroidonline videoappsmachine learningvirtual realitycloudhardware

See all employees

G

goo.gle/3DLEokh

10,001+ employees

Software Development

Mountain View, CA

Public Company

42.5M LinkedIn followers

Raised $26.1M

• Drive the technical win for complex workloads within Cloud AI to ensure rapid
• and successful adoption, primarily supporting the business cycle from
• technical evaluation through customer ramp.
• Combine business 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.

Required

• Bachelor's degreeor 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., 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 working with, or presenting to, technical stakeholders or
• executive leaders.

Preferred

• 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, TensorFlow, Jax,
• Ray), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g.,
• encoders, decoders, transformers), or using machine learning APIs.

• Bonus target
• Equity
• Health insurance
• Retirement benefits