AIEngJobs
RoleSuite
CompaniesRemoteAboutMethodologyContactPrivacy
Updated 2026-06-25 22:00 UTC·© 2025–2026 RoleSuite
← Back to listings

Lead GenAI Forward Deployed Engineer, YouTube

Google · San Bruno, CA, USA

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 solutions to solve them.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $186000 - $270000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

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 TypeScript) with practical experience building enterprise-grade applied AI solutions.
  • 4 years of experience working with teams and business stakeholders to create product roadmaps.
  • 4 years of experience as a Tech Lead or Engineering Manager.

Preferred qualifications:

  • Master’s degree or PhD in Artificial Intelligence, Computer Science, or a related field.
  • 4 years of experience with SRE, InfoSec, or DevOps, with experience building LLM evaluation (evals) pipelines, observability, and optimizing LLM-native metrics at scale.
  • 2 years of experience in vulnerability testing, security auditing, implementing AI safety guardrails, and ensuring enterprise accuracy.
  • Experience with enterprise AI data infrastructure (vector databases, embedding generation, search architectures, data readiness, and state-management).
  • Experience designing multi-agent systems (ReAct, tool-calling), MCP, and orchestration frameworks.
  • Knowledge of GTM, sales workflows, or CRMs, with experience driving technical adoption of zero-to-one AI products.

AI Engineering pay context

Based on 606 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $200K/year, with most offers between $162K and $237K (10th–90th percentile: $129K–$275K).

This posting lists $186K–$270K, above the $200K market median.

See the full AI Engineering salary breakdown →
Apply →

Other roles at Google

  • Senior Financial Analyst, Financial Planning and Analysis, Technical InfrastructureSunnyvale, CA, USA
  • Senior Strategy and Executive Operations Manager, Ads MarketingSan Francisco, CA, USA
  • Strategic Partnerships Development Manager, gStoreMountain View, CA, USA
  • Marketing Manager, YouTube Shopping, Latin America (English, Spanish, Portuguese)São Paulo, State of São Paulo, Brazil
  • Forward Deployed Engineer I, Google Cloud Consulting (French, German)Zürich, Switzerland
  • Customer Engineer, Google Distributed Cloud, EMEAMunich, Germany
  • Account Strategist, SBS Engage, Google Customer Solutions, Italy (English, Italian)Dublin, Ireland
  • Product Strategy and Operations Lead, Market IntelligenceSan Francisco, CA, USA
  • Product Manager II, Distribution MonetizationSan Jose, CA, USA
  • Senior Design Verification Engineer, Networking, Google CloudTel Aviv, Israel

More AI Engineering roles

  • Senior Machine Learning EngineerApple · Seattle
  • Senior Machine Learning Engineer - Ads Relevance & QualityApple · Cupertino
  • Machine Learning EngineerApple · Cupertino
  • Co-Op, ML Scientist for BiologyLila Sciences · San Francisco, CA USA
  • Senior Localization Engineer, Applied AITenable · Ireland - Office - Dublin
  • GenAI Project Lead in Washington, DCAccenture Federal Services · Washington, DC
  • Lead, AI Engineering & SDLC AutomationJobgether · US
  • Staff Engineer (ML Engineer)Graphcore · Cambridge, UK
  • Staff Engineer (ML Engineer)Graphcore · London, UK
  • Staff Engineer (ML Engineer)Graphcore · Bristol, UK