Google

Runs Search and YouTube and builds Gemini AI

Customer Engineer - Multiple Teams

Pre-Sales Solution EngineeringPosted on Nov 12

Full-timeNo salary listed

About the Job

Requirements

A bachelor's degree or equivalent practical experience is required.
Six years of experience with cloud-native architecture in a customer-facing or support role is required.
Experience with cloud engineering, on-premises engineering, virtualization, or containerization platforms is required.
Experience engaging with or presenting to technical stakeholders or executive leaders is required.
Experience in cloud migration or transformation projects in the public sector is required.
Experience in a technical pre-sales role, such as partner engineer, partner solution architect, solution architect, sales engineer, customer engineer, or field application engineer, is required.
Experience deploying AI models on air-gapped or on-premises high-performance computing systems is preferred.
Experience with large language model deployment frameworks such as vLLM, NVIDIA Triton, or Ollama, and agent development, is preferred.
Familiarity with cloud-native AI services such as Google Vertex AI is preferred.
Knowledge of the Open Worldwide Application Security Project for large language models or other security frameworks is preferred.

Responsibilities

Architect and manage large language model deployments across on-premises NVIDIA or AMD environments and cloud environments.
Audit multi-agent orchestration, agent construction, and vector databases to map data flows and enforce privilege boundaries.
Bridge local high-compute clusters and cloud AI services while maintaining a consistent security posture.
Use Docker and Kubernetes to orchestrate scalable inference and training environments, optimizing graphics processing unit utilization and resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the machine learning operations lifecycle.
Investigate and mitigate AI-specific threats, including prompt injection, jailbreaking, and data poisoning; map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.
Partner with technical sales teams to differentiate Google Cloud to customers and serve as their primary technical partner and trusted advisor.
Engage in technical-led conversations to understand customer business challenges, troubleshoot technical questions and roadblocks, and participate in proofs of concept and demonstrations.
Architect cross-pillar cloud solutions that address customer business challenges, drive the technical win, and define delivery and consumption plans.
Present practical solutions on Google Cloud to technical and business leaders.
Identify, pursue, and win new business workloads and drive penetration within existing workloads.
Apply expertise spanning infrastructure modernization, application modernization, and data analytics to demonstrate the value of the Google Cloud portfolio.

Desired Qualifications

Experience building long-term technical strategies to uncover new workloads with customers is preferred.

Architect and manage Large Language Model (LLM) deployments across on-premises (NVIDIA/AMD) and cloud (cloud computing platform, Google Cloud platform (GCP) environments. Audit multi-agent orchestration, agent construction, and vector databases to map data flows and enforce privilege boundaries.
Bridge local high-compute clusters and cloud AI services while maintaining a consistent security posture.
Use Docker and Kubernetes to orchestrate scalable inference and training environments, optimizing Graphics Processing Unit (GPU) utilization and resource isolation.
Protect model weights, secure data ingestion, and harden inference endpoints across the Machine Learning operations (MLOps) life-cycle.
Investigate and mitigate AI-specific threats (e.g., prompt injection, jailbreaking, data poisoning). Map testing findings to MITRE ATLAS, OWASP for LLMs, and STRIDE models.

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
6 years of experience with cloud native architecture in a customer-facing or support role.
Experience with cloud engineering, on-premise engineering, virtualization, or containerization platforms.
Experience engaging with, or presenting to, technical stakeholders or executive leaders.
Experience in cloud migration or transformation projects in the Public Sector.
Experience in a technical pre-sales role (e.g., partner engineer, partner solution architect, solution architect, sales engineer, customer engineer, field application engineer).

Preferred qualifications:

Experience deploying AI models on air-gapped or on-premises high-performance computing (HPC) systems.
Experience with Large Language Model (LLM) deployment frameworks such as vLLM, NVIDIA Triton, or Ollama and agent development.
Experience building long-term technical strategies to uncover new workloads with customers.
Familiarity with cloud-native AI services (e.g., cloud computing platform, Google Vertex AI).
Knowledge of Open Worldwide Application Security Project (OWASP) for LLMs or other security frameworks.

As a Platform Customer Engineer (CE), you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as the customer’s primary technical partner and trusted advisor, engaging in technical-led conversations to understand their business challenges. You will troubleshoot technical questions and roadblocks, engage in proofs-of-concepts and demos, and use your expertise to architect cross-pillar cloud solutions that solve these business challenges. You will drive the technical win and define the delivery and consumption plans. You will use your strategic acumen and presentation skills to engage with technical and business leaders, and persuasively present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills. You will focus on identifying, pursuing, and winning new business workloads and driving penetration within existing ones. You will have a breadth of technical expertise, spanning infrastructure modernization, application modernization, data analytics and more. You will blend sales expertise, market knowledge and direct technical engagement to prove the value of the Google Cloud portfolio.

This role will be based in Sao Paulo or Brasilia.

Please submit your resume in English - we can only consider applications submitted in this language.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following:

In-office locations: São Paulo, Brazil.
Remote location(s): Brazil.

Bachelor's degree or equivalent practical experience.
6 years of experience with cloud native architecture in a customer-facing or support role.
Experience with cloud engineering, on-premise engineering, virtualization, or containerization platforms.
Experience engaging with, or presenting to, technical stakeholders or executive leaders.
Experience in cloud migration or transformation projects in the Public Sector.
Experience in a technical pre-sales role (e.g., partner engineer, partner solution architect, solution architect, sales engineer, customer engineer, field application engineer).

About the Company

Google

Runs Search and YouTube and builds Gemini AI

Google runs the world's most used search engine and free services such as YouTube, Android, and Gmail, and it builds the Gemini AI models that work inside them. In 2017, its researchers invented the transformer, the neural network design behind ChatGPT and most other AI chatbots. People use these services without paying, and Google earns most of its money from ads placed beside search results and YouTube videos. Businesses rent computing power and Gemini models through Google Cloud, and Google also sells subscriptions and Pixel phones. Larry Page and Sergey Brin founded Google in 1998 as Stanford PhD students; it is based in Mountain View, California, United States, and is the main business of parent company Alphabet.

Company size: 10,001+
Company stage: IPO
Headquarters: Mountain View, CA
Founded: 1998

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