Customer Engineer, Cloud AI, Telco and Gaming, Google Cloud

Google•Apply•Published 1 hours ago•First seen 1 hours ago

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) for Telco and Gaming (T&G) 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 specialized workloads. You will leverage your expertise in our product areas, in partnership with Platform CEs, and you will be writing code to develop prototypes, proofs-of-concept, and demos to sell new, highly specialized solutions to customers. You will solve Artificial Intelligence (AI)-centered 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 prowess, market knowledge, and technical engagement to prove the value of the Google Cloud portfolio.

The US base salary range for this full-time position is $102,000-$146,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

Drive the technical win for workloads within Cloud AI to ensure adoption, primarily supporting the sales cycle from technical evaluation through customer ramp.
Combine sales strategies and development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
Provide 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.
4 years of experience with cloud native architecture in industry or 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), and integrating large models into autonomous workflows via advanced Application Programming Interface (API) prompting and Retrieval-Augmented Generation (RAG).
Experience engaging with, and presenting to, technical stakeholders and 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 with frameworks for deep learning (e.g., PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g., TPUs, GPUs), model architectures (e.g., encoders, decoders, transformers)/using machine learning APIs.
Experience developing distributed software/infrastructure and leveraging technical proficiencies for customer-facing prototyping and workshops.
Experience with customer-facing sales for Telco and Gaming industries.
Ability to quickly learn and implement emerging cloud/IT technologies and methodologies.