Customer Engineer, Cloud AI, Google Cloud

Google; Chicago (IL); Hybrid; USD 192,000 - 267,000; Full time

Job summary

Google Cloud is seeking a Customer Engineer specializing in Cloud AI to partner with technical sales teams and differentiate Google Cloud for customers. You will accelerate technical wins, develop prototypes and proofs-of-concept, and solve AI-centered challenges with stakeholders.

You will present practical, scalable AI workloads and influence product direction through customer feedback. You will collaborate with Platform CEs and Engineering teams, write code for demos, and help customers adopt

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 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.

Responsibilities

• Drive the technical win for complex workloads within Cloud AI to ensure rapid adoption and customer ramp.
• Provide deep technical consultation and build lasting customer relationships.
• Develop prototypes, proofs-of-concept, and demos to sell specialized solutions.
• Collaborate with GTM teams to create reusable solutions and assets.
• Document and prioritize customer feature requests in product/engineering systems.

Skills

Cloud architecture

Customer enablement

ML model development

AI agent orchestration

Executive stakeholder communication

Education

Bachelor's degree or equivalent practical experience

Master's degree (preferred)

Tools

PyTorch

TensorFlow

Jax

Ray

TPUs/GPUs

LangGraph

CrewAI

AutoGen

Job description

Customer Engineer, Cloud AI, Google Cloud

Google

New York, NY, USA; Cambridge, MA, USA; +2 more

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Cambridge, MA, USA; Chicago, IL, USA; Detroit, MI, USA.

Minimum qualifications:

• 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 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 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.

About the job

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As a Practice Customer Engineer (CE) with a specialty in Cloud AI, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your deep expertise in our most strategic product areas, in partnership with Platform CEs, in writing code to developing prototypes, proofs-of-concept, and demos to sell new, highly specialized solutions to customers. You will solve AI-centered customer challenges 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 prowess, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $192000 - $267000 (USD) + 42.86% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• 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.