Customer Engineer, Platform, Public Sector, Google Cloud

About the job

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.

Responsibilities

• 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.

Qualifications

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.