Senior Cloud AI Solutions Engineer

Google LLC; New York (NY); On-site; USD 152,000 - 221,000; Full time

Job summary

Google Cloud is seeking a Customer Engineer specializing in Cloud AI to partner with technical sales teams, accelerate adoption of complex workloads, and deliver practical, scalable solutions for customers.

You will develop prototypes and demos, engage with executives and technical stakeholders, and collaborate with product and engineering teams to translate customer needs into winning architectures and reusable assets.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 10 years of cloud-native architecture experience in a customer-facing or support role.
• Experience with AI agent orchestration frameworks (LangGraph, CrewAI, AutoGen) and agentic design patterns and integrating models via 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.

Responsibilities

• Differentiate Google Cloud to customers and accelerate technical wins.
• Prototype, POC, and demos for complex workloads.
• Collaborate with Platform CEs, product marketing, and engineering on industry trends and customer needs.
• Provide technical consultation and build lasting customer relationships.
• Contribute to reusable assets and GTM initiatives from customer engagements.

Skills

Cloud architecture

AI agent orchestration

API prompting

ML deployment

Stakeholder communication

Prototyping demos

Education

Bachelor's degree or equivalent practical experience

Master's degree

Tools

LangGraph

CrewAI

AutoGen

Vector databases

APIs

Job description

Google Cloud is seeking a Customer Engineer specializing in Cloud AI to partner with technical sales teams, accelerate adoption of complex workloads, and deliver practical, scalable solutions for customers.

You will develop prototypes and demos, engage with executives and technical stakeholders, and collaborate with product and engineering teams to translate customer needs into winning architectures and reusable assets.