Lead GenAI Forward Deployed Engineer, YouTube GTM Operations
AI summary of the role
Lead GenAI Forward Deployed Engineer on YouTube's GTM AI Accelerator team, driving AI transformation of YouTube Business GTM operations.
What you’ll do
- Build GenAI PoCs (LLMs, RAG, agentic frameworks) to demonstrate feasibility to stakeholders.
- Serve as engineering Lead delivering complex AI applications, transitioning rapid prototypes to production-grade systems (e.g., multi-agent systems, MCP servers).
- Act as a trusted engineering partner to product management and stakeholders, co-creating tool roadmaps for YouTube's business operations.
- Author technical designs, write clean/maintainable code, build front-ends, and deliver from scoping to deployment.
What you’ll bring
- Bachelor's degree in CS, EE, Math, or related quantitative field, or equivalent practical experience.
- 9 years of experience building APIs or web applications, designing scalable microservice or system architectures.
- 8 years of experience in full-stack development using Python, Go, Java, C++, or TypeScript with enterprise-grade applied AI solutions.
- 4 years of experience working with teams and business stakeholders to create product roadmaps.
Technologies
GenAI · LLMs · RAG · agentic frameworks · multi-agent systems · MCP servers · Python · Go · Java · C++ · TypeScript · vector databases
About Google
Builds global consumer, ads, cloud, developer and AI platforms spanning Search, YouTube, Android, Workspace and Gemini.
Public
Source and classification
Internal deployment & tooling · Evidence for this classification:
mission is to operate as a high-velocity, horizontal transformation engine, partnering directly with YouTube Biz GTM business domains to fundamentally redesign legacy workflows from scratch and leverage applied AI to drive direct business impact for YouTube. We operate at the intersection of consulting, product strategy, applied AI and systems engineering. We identify the most painful operational bottlenecks across the organization and rapidly deploy intelligent, enterprise-grade AI powered solutions to solve them. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $186000 - $269000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Build GenAI PoCs (LLMs, RAG, agentic frameworks) to demonstrate feasibility to stakeholders, translating ambiguous business problems
More from the job description
About the job In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration, and more). It's an exciting time to join YouTube's Go To Market Organization's AI Accelerator team, devising the AI transformation for YouTube Business GTM operations. The AI Accelerator is a newly formed task group dedicated to driving AI transformation across the organization. Our mission is to operate as a high-velocity, horizontal transformation engine, partnering directly with YouTube Biz GTM business domains to fundamentally redesign legacy workflows from scratch and leverage applied AI to drive direct business impact for YouTube. We operate at the intersection of consulting, product strategy, applied AI and systems engineering. We identify the most painful operational bottlenecks across the organization and rapidly deploy intelligent, enterprise-grade AI powered solut [... source excerpt omitted ...] ding job-related skills, experience, and relevant education or training. US: $186000 - $269000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Build GenAI PoCs (LLMs, RAG, agentic frameworks) to demonstrate feasibility to stakeholders, translating ambiguous business problems into software solutions. Serve as engineering Lead delivering complex AI applications, transitioning rapid prototypes to production-grade systems (e.g., multi-agent systems, MCP servers) that drive Return on Investment (ROI). Act as a trusted engineering partner to product managements and stakeholders, co-creating tool roadmaps that enable YouTube's business [... source excerpt omitted ...] pipelines and observability frameworks to resolve AI bottlenecks (data readiness, system integration, state-management) while ensuring accuracy, safety, compliance, and latency. Qualifications Minimum qualifications: Bachelor's degree in Computer Science, Electrical Engineering, Math, a related quantitative field, or equivalent practical experience in software development. 9 years of experience building APIs or web applications, designing scalable microservice or system architectures, including backend data pipelines, distributed systems, and data privacy. 8 years of experience in full-stack development using one or more programming languages (e.g., Python, Go, Java, C++, or Type
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