GenAI Solutions Lead — YouTube GTM Operations

Google; Mountain View (CA); On-site; USD 186,000 - 269,000; Full time

Job summary

Google is seeking a senior engineering leader to join the AI Accelerator team within YouTube's Go-To-Market organization in Mountain View, CA. You will drive AI transformation, build production-grade multi-agent and GenAI systems, and partner with product leadership to shape roadmaps that unlock business value.

You will lead design and implementation of scalable APIs, data pipelines, and observability frameworks, while ensuring performance, safety, and compliance in enterprise AI deployments.

Qualifications

• Bachelor's degree in CS, EE, math or equivalent practical experience.
• 9+ years building APIs or web apps, designing scalable systems and pipelines.
• 8+ years full-stack dev with Python/Go/Java/C++/TypeScript, enterprise AI solutions.
• 4 years coordinating with stakeholders to build product roadmaps.
• 4 years as Tech Lead or Engineering Manager.

Responsibilities

• Build GenAI PoCs for stakeholders, translating business problems into software solutions.
• Lead engineering efforts delivering production-grade AI applications.
• Partner with product mgmt to co-create tool roadmaps for YouTube's business ops.
• Write technical designs, code, and deliver from scoping to deployment.
• Build eval pipelines and observability to ensure AI accuracy, safety and latency.

Skills

API design

Full-stack development

Team leadership

Roadmap planning

Education

Bachelor's degree in Computer Science or related field

Tools

Python

Go

Java

TypeScript

C++

Job description

Google is seeking a senior engineering leader to join the AI Accelerator team within YouTube's Go-To-Market organization in Mountain View, CA. You will drive AI transformation, build production-grade multi-agent and GenAI systems, and partner with product leadership to shape roadmaps that unlock business value.

You will lead design and implementation of scalable APIs, data pipelines, and observability frameworks, while ensuring performance, safety, and compliance in enterprise AI deployments.