Senior Cloud AI Engineer — Prototypes & Demos

Google; 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 accelerate technical wins and adoption of complex workloads. You will partner with technical sales, write code for prototypes, and deliver demos that showcase new AI solutions to customers.

You will liaise with product and engineering teams, understand business needs, and present practical, scalable AI approaches. Strong communication and executive-level engagement are essential.

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 and agentic design patterns.
• Experience with ML model development and deployment.
• Experience communicating with technical stakeholders and executives.
• Experience using programming languages to design demos and workshops.

Responsibilities

• Drive the technical win for Cloud AI workloads throughout the customer lifecycle.
• Provide deep technical consultation and build lasting customer relationships.
• Develop prototypes, POCs, and demos to promote specialized solutions.
• Collaborate with GTM and engineering to document and prioritize feature requests.
• Present practical, customer-focused solutions and accelerate adoption.

Skills

Cloud native architecture

AI agent orchestration

Agentic design patterns

API prompting and RAG

ML model development & deployment

Stakeholder communication

Prototyping & demos

Education

Bachelor's degree or equivalent

Master's degree preferred

Tools

LangGraph

CrewAI

AutoGen

Job description

Google Cloud is seeking a Customer Engineer specializing in Cloud AI to accelerate technical wins and adoption of complex workloads. You will partner with technical sales, write code for prototypes, and deliver demos that showcase new AI solutions to customers.

You will liaise with product and engineering teams, understand business needs, and present practical, scalable AI approaches. Strong communication and executive-level engagement are essential.