Customer Engineer, Cloud AI, Google Cloud

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.

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, to be writing code to develop 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 expertise, 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: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* 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.