Customer Engineer III, 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 AI agent orchestration frameworks (e.g., LangGraph, CrewAI,

AutoGen), agentic design patterns (e.g., tool-use, multi-agent

collaboration), and integrating models into autonomous workflows via advanced

API prompting and RAG.

* Experience with machine learning model development and deployment.

* Experience engaging with, and presenting to, technical stakeholders and

executive leaders.

* Experience using programming languages to design demos, prototypes, or

workshops for customers.

PREFERRED QUALIFICATIONS:

* Master's degree in Computer Science, Engineering, Mathematics, a technical

field, or equivalent practical experience.

* Experience in architecting and developing software or infrastructure for

scalable, distributed systems.

* Experience in building machine learning solutions and leveraging specific

machine learning architectures (e.g., LLMs, Diffusion, and Multimodal

Models).

* Experience developing and deploying Generative AI applications, with a focus

on implementing RAG pipelines, integrating vector databases, and

orchestrating LLM interactions via APIs.

* Experience in the hospitality, travel, power, manufacturing or energy

industry.

* Ability to learn quickly, understand, and work with new emerging

technologies, methodologies, and solutions in the cloud/IT technology space.

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 Customer Engineer (CE) with a specialty in Cloud Artificial Intelligence

(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 product areas, in partnership with

Platform Customer Engineers (CEs), to be writing code to develop prototypes,

proofs-of-concept (POCs), and demos to promote new specialized solutions to

customers. You will solve AI customer issues 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.

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 workloads within Cloud AI to ensure rapid and

successful adoption, primarily supporting the business cycle from technical

evaluation through customer ramp.

* Combine business strategies, 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 (GTM) team.

* Work within product and engineering management systems to document,

prioritize, and drive resolution of customer feature requests and issues.